Programmierung
Java All-in-One For Dummies
Get started writing Java® code—the easy way Java® code is the go-to language for developing Android apps and all sorts of other things. With Java All-in-One For Dummies, you can write your first lines of code in Java and work your way to advanced stuff like Internet of Things (IoT) programming, JavaFX, and Java for the web. Easy-to-follow instructions, fun practice, and a time-tested instructional approach will shorten your learning journey. With eight mini-books in one, consider this the only Java book you’ll need as your take your knowledge to the next level, and the next, and the next. 8 Mini-books Inside… Java BasicsProgramming BasicsObject-Oriented ProgrammingStrings and Other Data TypesData StructuresAlgorithmsProgramming TechniquesJavaFX A beginning coder’s resource for learning the most popular coding language With Java All-in-One For Dummies, you get 8 books in one, for the most well-rounded Java knowledge on the market. Updated for Java 19, this book includes all the major changes to the programming language, so you won’t fall behind. Start by learning the basics of Java—you can do it, even if you’ve never written a line of code in your life. Then go in-depth, with all the info you need on object-oriented programming, Java FX, Java web development, and beyond. Grab a hot cup of java and settle in to learn some Java, with friendly For Dummies guidance! Learn the basics of computer programming and get started with the Java languageMaster strings, arrays, and collectionsDiscover the most recent Java updates and the latest in programming techniquesLaunch or further your career as a coder with easy-to-follow instruction This is the go-to Dummies guide for future and current coders who need an all-inclusive guide Java to take their knowledge to the next level. Introduction 1 Book 1: Java Basics 5 Chapter 1: Welcome to Java 7 Chapter 2: Installing and Using Java Tools 17 Chapter 3: Working with TextPad 31 Book 2: Programming Basics 37 Chapter 1: Java Programming Basics 39 Chapter 2: Working with Variables and Data Types 59 Chapter 3: Working with Numbers and Expressions 97 Chapter 4: Making Choices 127 Chapter 5: Going Around in Circles (or, Using Loops) 149 Chapter 6: Pulling a Switcheroo 177 Chapter 7: Adding Some Methods to Your Madness 195 Chapter 8: Handling Exceptions 215 Book 3: Object-Oriented Programming 237 Chapter 1: Understanding Object-Oriented Programming 239 Chapter 2: Making Your Own Classes 253 Chapter 3: Working with Statics 273 Chapter 4: Using Subclasses and Inheritance 283 Chapter 5: Using Abstract Classes and Interfaces 305 Chapter 6: Using the Object and Class Classes 327 Chapter 7: Using Inner Classes and Anonymous Classes 355 Chapter 8: Working with Packages and the Java Module System 365 Book 4: Strings and Other Data Types 387 Chapter 1: Working with Strings 389 Chapter 2: Using Regular Expressions 411 Chapter 3: Working with Dates and Times 429 Chapter 4: Using the BigDecimal Class 451 Book 5: Data Structures 471 Chapter 1: Introducing Data Structures 473 Chapter 2: Using Arrays 503 Chapter 3: Using the ArrayList Class 535 Chapter 4: Using the LinkedList Class 549 Chapter 5: Creating Generic Collection Classes 561 Chapter 6: Using Maps and Trees 575 Book 6: Algorithms 595 Chapter 1: Introducing Algorithms 597 Chapter 2: Using Recursion 613 Chapter 3: Sorting 625 Chapter 4: Searching 637 Book 7: Programming Techniques 657 Chapter 1: Programming Threads 659 Chapter 2: Using Functional Programming and Lambda Expressions 689 Chapter 3: Consuming Web Services with HttpClient 705 Book 8: JavaFX 727 Chapter 1: Hello, JavaFX! 729 Chapter 2: Handling Events 751 Chapter 3: Setting the Stage and Scene Layout 769 Chapter 4: Using Layout Panes to Arrange Your Scenes 791 Chapter 5: Getting Input from the User 825 Chapter 6: Choosing from a List 841 Index 869 Doug Lowe is an accomplished technology writer of more than 30 books. He is a tech guru on all things computer programming. His expertise covers networking, Microsoft® Office, programming, and computer building. He is the author of the previous edition of Java All-in-One For Dummies.
Python 3 - Das umfassende Handbuch (7. Auflage)
Das Python-Handbuch zum Lernen und Nachschlagen! Ob Sie erst anfangen, mit Python zu arbeiten oder bei Ihrer Arbeit etwas nachschlagen möchten – in diesem Buch lernen Sie alles, was Sie zu Python 3 wissen müssen. Angefangen mit einer Einführung in die Sprache bietet es eine Sprachreferenz, die Beschreibung der Standardbibliothek und ausführliche Informationen zu professionellen Themen und verschiedenen Anwendungsbereichen. Von der GUI-Programmierung über die Webentwicklung bis zu Data Science: Dieses Buch macht den persönlichen Werkzeugkasten perfekt.Aus dem Inhalt: Sprachgrundlagen und objektorientierte ProgrammierungReguläre AusdrückeDatums- und ZeitfunktionenThread-ProgrammierungGUI-ProgrammierungWebentwicklung mit DjangoMigration von Python 2.x nach 3Mathematische ModuleWissenschaftliches RechnenData ScienceAutoren:Dr. Johannes Ernesti hat am Karlsruher Institut für Technologie (KIT) in angewandter Mathematik promoviert.Dr. Peter Kaiser hat am Karlsruher Institut für Technologie (KIT) in humanoider Robotik promoviert. Seit Mai 2019 arbeitet er als Research Scientist bei DeepL.Leseprobe (PDF-Link)
Java für Dummies (8. Auflg.)
Sie wollen in Java einsteigen oder Ihre Kenntnisse erweitern? »Java für Dummies« ist gleichzeitig Lehrbuch und unverzichtbares Nachschlagewerk für alle Java-Programmierer. Basiswissen zur objektorientierten Programmierung wird genauso vermittelt wie das Prinzip der Wiederverwendbarkeit von Programmbausteinen. Außerdem lernen Sie, wann Variablen innerhalb oder außerhalb von Methoden deklariert werden sollten, wo die Grenzen von Arrays liegen und wie Code mit Exceptions absturzsicher gemacht wird. Diese Auflage von »Java für Dummies« berücksichtigt die Neuerungen der Version Java 17. Barry Burd ist Mathematiker und Professor für Informatik. Er hat alle Auflagen von "Java für Dummies" und "Mit Java programmieren lernen für Dummies" verfasst und schreibt häufig Artikel über Java für Online-Publikationen.Einleitung 23TEIL I: LOS GEHT’S 27Kapitel 1: Alles über Java 29Kapitel 2: Alles über Software 41Kapitel 3: Die grundlegenden Bausteine verwenden 53TEIL II: EIGENE JAVA-PROGRAMME SCHREIBEN 75Kapitel 4: Das Optimum aus Variablen und ihren Werten herausholen 77Kapitel 5: Den Programmablauf mit entscheidungsfindenden Befehlen steuern 115Kapitel 6: Den Programmablauf mit Schleifen steuern 151TEIL III: DAS GROẞE GANZE: OBJEKTORIENTIERTE PROGRAMMIERUNG 169Kapitel 7: Die Sache mit der objektorientierten Programmierung 171Kapitel 8: Zeit und Geld sparen: Code wiederverwenden 211Kapitel 9: Neue Objekte entwerfen 243TEIL IV: INTELLIGENTE JAVA-TECHNIKEN 267Kapitel 10: Variablen und Methoden richtig platzieren 269Kapitel 11: Arrays verwenden, um mit Werten zu jonglieren 301Kapitel 12: Sammlungen und Streams verwenden (wenn Arrays nicht mehr ausreichen) 327Kapitel 13: Gut aussehen, wenn sich die Dinge unerwartet ändern 357Kapitel 14: Namen in Programmteilen gemeinsam nutzen 385Kapitel 15: Referenztypen 411Kapitel 16: Jonglieren mit Java 429Kapitel 17: Datenbankverbindungen aufbauen und nutzen mit Java 449TEIL V: DER TOP-TEN-TEIL 459Kapitel 18: Zehn Ratschläge für neue Softwareentwickler 461Kapitel 19: Zehn Websites für Java 467Abbildungsverzeichnis 469Stichwortverzeichnis 475
R All-in-One For Dummies
A DEEP DIVE INTO THE PROGRAMMING LANGUAGE OF CHOICE FOR STATISTICS AND DATAWith R All-in-One For Dummies, you get five mini-books in one, offering a complete and thorough resource on the R programming language and a road map for making sense of the sea of data we're all swimming in. Maybe you're pursuing a career in data science, maybe you're looking to infuse a little statistics know-how into your existing career, or maybe you're just R-curious. This book has your back. Along with providing an overview of coding in R and how to work with the language, this book delves into the types of projects and applications R programmers tend to tackle the most. You'll find coverage of statistical analysis, machine learning, and data management with R.* Grasp the basics of the R programming language and write your first lines of code* Understand how R programmers use code to analyze data and perform statistical analysis* Use R to create data visualizations and machine learning programs * Work through sample projects to hone your R coding skillThis is an excellent all-in-one resource for beginning coders who'd like to move into the data space by knowing more about R.JOSEPH SCHMULLER is a cognitive scientist and statistical analyst. His recent work in the For Dummies series includes the 5th edition of Statistical Analysis with Excel For Dummies along with Statistical Analysis with R For Dummies and R Projects For Dummies.Introduction 1BOOK 1: INTRODUCING R 5Chapter 1: R: What It Does and How It Does It 7Chapter 2: Working with Packages, Importing, and Exporting 37BOOK 2: DESCRIBING DATA 51Chapter 1: Getting Graphic 53Chapter 2: Finding Your Center 93Chapter 3: Deviating from the Average 103Chapter 4: Meeting Standards and Standings 113Chapter 5: Summarizing It All 125Chapter 6: What’s Normal? 145BOOK 3: ANALYZING DATA 163Chapter 1: The Confidence Game: Estimation 165Chapter 2: One-Sample Hypothesis Testing 181Chapter 3: Two-Sample Hypothesis Testing 207Chapter 4: Testing More than Two Samples 233Chapter 5: More Complicated Testing 257Chapter 6: Regression: Linear, Multiple, and the General Linear Model 279Chapter 7: Correlation: The Rise and Fall of Relationships 315Chapter 8: Curvilinear Regression: When Relationships Get Complicated 335Chapter 9: In Due Time 359Chapter 10: Non-Parametric Statistics 371Chapter 11: Introducing Probability 393Chapter 12: Probability Meets Regression: Logistic Regression 415BOOK 4: LEARNING FROM DATA 423Chapter 1: Tools and Data for Machine Learning Projects 425Chapter 2: Decisions, Decisions, Decisions 449Chapter 3: Into the Forest, Randomly 467Chapter 4: Support Your Local Vector 483Chapter 5: K-Means Clustering 503Chapter 6: Neural Networks 519Chapter 7: Exploring Marketing 537Chapter 8: From the City That Never Sleeps 557BOOK 5: HARNESSING R: SOME PROJECTS TO KEEP YOU BUSY 573Chapter 1: Working with a Browser 575Chapter 2: Dashboards — How Dashing! 603Index 639
Practical Debugging at Scale
Overhaul your debugging techniques and master the theory and tools needed to debug and troubleshoot cloud applications in production environments. This book teaches debugging skills that universities often avoid, but that typically consume as much as 60% of our time as developers. The book covers the use of debugger features such as tracepoints, object marking, watch renderers, and more. Author Shai Almog presents a scientific approach to debugging that is grounded in theory while being practical enough to help you to chase stubborn bugs through the maze of a Kubernetes deployment.Practical Debugging at Scale assumes a polyglot environment as is common for most enterprises, but focuses on JVM environments. Most of the tooling and techniques described are applicable to Python, Node, and other platforms, as well as to Java and other JVM languages. The book specifically covers debugging in production, an often-neglected discipline but an all too painful reality. You’ll learn modern techniques around observability, monitoring, logging, and full stack debugging that you can put to immediate use in troubleshooting common ailments in production environments.YOU WILL LEARN:* The scientific method underlying the process of debugging* Debugger capabilities such as tracepoints and marker objects* The correct use of less understood features such as exception breakpoints* Techniques for tracing issues in production Kubernetes environments* Observability and monitoring to resolve production problems* Industry best practices for common tooling such as logging * Profiling to understand performance and memory problems WHO THIS BOOK IS FORDevelopers in Java and JVM-related languages who want to improve their debugging skills and production reliability; and developers of cloud applications who are facing the pain of production bugs that are hard to replicate and fixSHAI ALMOG is an entrepreneur, open source hacker, speaker, author, blogger, Java rockstar, and more. He is a former Sun (later Oracle) developer with more than 30 years of experience. Shai has built JVMs, development tools, mobile phone environments, banking systems, startup/enterprise backends, user interfaces, development frameworks, and much more. He speaks at conferences all over the world and has shared the stage with luminaries such as James Gosling (father of Java). Shai is an award-winning, highly rated speaker with deep technical experience to share and he has a knack for engaging his audience. IntroductionPART I. BASICS1. Know Your Debugger2. The Checklist3. The Auxiliary Tools4. Logging, Testing, and Fail Fast5. Time Travel DebuggingPART II. THE MODERN PRODUCTION ENVIRONMENT6. Debugging Kubernetes7. Serverless Debugging8. Fullstack Debugging9. Observability and Monitoring10. Developer ObservabilityPART III. IN PRACTICE11. Tools of Learning12. Performance and Memory13. Security14. Bug Strategies
Pro Deep Learning with TensorFlow 2.0
This book builds upon the foundations established in its first edition, with updated chapters and the latest code implementations to bring it up to date with Tensorflow 2.0.Pro Deep Learning with TensorFlow 2.0 begins with the mathematical and core technical foundations of deep learning. Next, you will learn about convolutional neural networks, including new convolutional methods such as dilated convolution, depth-wise separable convolution, and their implementation. You’ll then gain an understanding of natural language processing in advanced network architectures such as transformers and various attention mechanisms relevant to natural language processing and neural networks in general. As you progress through the book, you’ll explore unsupervised learning frameworks that reflect the current state of deep learning methods, such as autoencoders and variational autoencoders. The final chapter covers the advanced topic of generative adversarial networks and their variants, such as cycle consistency GANs and graph neural network techniques such as graph attention networks and GraphSAGE.Upon completing this book, you will understand the mathematical foundations and concepts of deep learning, and be able to use the prototypes demonstrated to build new deep learning applications.WHAT YOU WILL LEARN* Understand full-stack deep learning using TensorFlow 2.0* Gain an understanding of the mathematical foundations of deep learning * Deploy complex deep learning solutions in production using TensorFlow 2.0* Understand generative adversarial networks, graph attention networks, and GraphSAGEWHO THIS BOOK IS FOR:Data scientists and machine learning professionals, software developers, graduate students, and open source enthusiasts.SANTANU PATTANAYAK works as a Senior Staff Machine Learning Specialist at Qualcomm Corp R&D and is the author of Quantum Machine Learning with Python, published by Apress. He has more than 16 years of experience, having worked at GE, Capgemini, and IBM before joining Qualcomm. He graduated with a degree in electrical engineering from Jadavpur University, Kolkata and is an avid math enthusiast. Santanu has a master’s degree in data science from the Indian Institute of Technology (IIT), Hyderabad. He also participates in Kaggle competitions in his spare time, where he ranks in the top 500. Currently, he resides in Bangalore with his wife.Chapter 1: Mathematical FoundationsChapter Goal: Setting the mathematical base for machine learning and deep learning .No of pages 100Sub -Topics1. Linear algebra2. Calculus3. Probability4. Formulation of machine learning algorithms and optimization techniques.Chapter 2: Introduction to Deep learning Concepts and Tensorflow 2.0Chapter Goal: Setting the foundational base for deep learning and introduction to Tensorflow 2.0 programming paradigm.No of pages: 75Sub - Topics:5. Deep learning and its evolution.6. Evolution of the learning techniques: from perceptron based learning to back-propagation7. Different deep learning objectives functions for supervised and unsupervised learning.8. Tensorflow 2.09. GPUChapter 3: Convolutional Neural networksChapter Goal: The mathematical and technical aspects of convolutional neural networkNo of pages: 801. Convolution operation2. Analog and digital signal3. 2D and 3D convolution, dilation and depth-wise separable convolution4. Common image processing filter5. Convolutional neural network and components6. Backpropagation through convolution and pooling layers7. Translational invariance and equivariance8. Batch normalization9. Image segmentation and localization methods (Moved from advanced Neural Network to here, to make room for Graph Neural Networks )Chapter 4: Deep learning for Natural Language ProcessingChapter Goal: Deep learning methods and natural language processing No of pages:Sub - Topics:1. Vector space model2. Word2Vec3. Introduction to recurrent neural network and LSTM4. Attention5. Transformer network architecturesChapter 5: Unsupervised Deep Learning MethodsChapter Goal: Foundations for different unsupervised deep learning techniquesNo of pages: 60Sub - Topics:1. Boltzmann distribution2. Bayesian inference3. Restricted Boltzmann machines4. Auto Encoders and variation methodsChapter 6: Advanced Neural NetworksChapter Goal: Generative adversarial networks and graph neural networksNo of pages: 70Sub - Topics:1. Introduction to generative adversarial networks2. CycleGAN, LSGAN Wasserstein GAN3. Introduction to graph neural network4. Graph attention network and graph SAGEChapter 7: Reinforcement LearningChapter Goal: Reinforcement Learning using Deep LearningNo of pages: 50Sub - Topics:1. Introduction to reinforcement learning and MDP formulation2. Value based methods3. DQN4. Policy based methods5. Reinforce and actor critic network in policy based formulations6. Transition-less reinforcement learning and bandit methods
Internet of Things Using Single Board Computers
Rapidly prototype and program new IoT and Edge solutions using low-cost Maker tech, such as those from Arduino, Raspberry Pi and Nvidia. With a focus on the electronics, this book allows experienced computer science students as well as researchers, practitioners, and even hobbyists to dive right into actual engineering of prototypes and not just theoretical programming and algorithms.You'll learn to interface sensors, work with various communication mediums, incorporate wired and wireless communication protocols, and more with these single board computers. All while working in the popular Python programming language. Additionally, you’ll discover both scripting-based and drag and drop solutions for different problems. As well as a variety of useful, data gathering approaches. Then you can apply what you’ve learned to IoT projects and troubleshooting Industry 4.0 problems.The rapid growth of technology and new development initiatives has made the Internet of Things and Edge analytics an inevitable platform in all engineering domains. The need for sophisticated and ambient environments controlled by tech has resulted in an exponential growth of automation and artificial intelligence. Internet of Things Using Single Board Computers reflects these recent developments while providing a low-cost, easy ramp into the fields of IoT using single board computers and Python programming.WHAT YOU'LL LEARN* Program Arduino, Raspberry Pi, and Nvidia boards for rapid prototyping in IoT and Edge environments* Interface sensors, communication mediums, and wired and wireless communications into your programs and projects.* Study practical applications of these low-cost solutions in fields such as home automation, smart cities, electrical vehicle charging, and more.WHO THIS BOOK IS FOREngineers and hobbyists working on Internet of Things prototypes and applications. Basic skills in electronics and a working knowledge of Python are recommended. Engineers and scientists working on smart environment projects and smart city applications will also benefit.DR. G. R. KANAGACHIDAMBARESAN completed his Ph.D. at Anna University Chennai in 2017. He is currently an Associate Professor in the Department of CSE at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology. His main research interests include Body Sensor Networks and Fault Tolerant Wireless Sensor Networks. He has published several articles and undertaken consultancy activities for leading MNC companies. He has also guest-edited special issue volumes and books and served as an editorial review board member for peer-reviewed journals. He is presently working on several government sponsored research projects like ISRO, DBT, and DST. Presently, he is the Editor in chief for the Next Generation Computer and Communication Engineering series. INTERNET OF THINGS USING SINGLE BOARD COMPUTERSChapter 1: An Overview of IoTChapter 2: IoT ArchitectureChapter 3: Programming Through pythonChapter 4: Wireless Technology for IoTChapter 5: Building IoT with Raspberry PiChapter 6: Home AutomationChapter 7: Smart Cities and Smart GridsChapter 8: Electric Vehicle ChargingChapter 9: Agriculture
Numerical Methods Using Kotlin
This in-depth guide covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started.In this book, you'll implement numerical algorithms in Kotlin using NM Dev, an object-oriented and high-performance programming library for applied and industrial mathematics. Discover how Kotlin has many advantages over Java in its speed, and in some cases, ease of use. In this book, you’ll see how it can help you easily create solutions for your complex engineering and data science problems.After reading this book, you'll come away with the knowledge to create your own numerical models and algorithms using the Kotlin programming language.WHAT YOU WILL LEARN* Program in Kotlin using a high-performance numerical library* Learn the mathematics necessary for a wide range of numerical computing algorithms* Convert ideas and equations into code* Put together algorithms and classes to build your own engineering solutions* Build solvers for industrial optimization problems* Perform data analysis using basic and advanced statisticsWHO THIS BOOK IS FORProgrammers, data scientists, and analysts with prior experience programming in any language, especially Kotlin or Java.HAKSUN LI, PHD, is founder of NM Group, a scientific and mathematical research company. He has the vision of “Making the World Better Using Mathematics”. Under his leadership, the firm serves worldwide brokerage houses and funds, multinational corporations and very high net worth individuals. Haksun is an expert in options trading, asset allocation, portfolio optimization and fixed-income product pricing. He has coded up a variety of numerical software, including SuanShu (a library of numerical methods), NM Dev (a library of numerical methods), AlgoQuant (a library for financial analytics), NMRMS (a portfolio management system for equities), and supercurve (a fixed-income options pricing system). Prior to this, Haksun was a quantitative trader/quantitative analyst with multiple investment banks. He has worked in New York, London, Tokyo, and Singapore. Additionally, Haksun is the vice dean of the Big Data Finance and Investment Institute of Fudan University, China. He was an adjunct professor with multiple universities. He has taught at the National University of Singapore (mathematics), Nanyang Technological University (business school), Fudan University (economics), as well as Hong Kong University of Science and Technology (mathematics). Dr. Haksun Li has a B.S. and M.S. in pure and financial mathematics from the University of Chicago, and an M.S. and a PhD in computer science and engineering from the University of Michigan, Ann Arbor.1: Introduction to Numerical Methods in Kotlin.-2: Linear Algebra.-3: Finding Roots of Equations.-4: Finding Roots of Systems of Equations.-5: Curve Fitting and Interpolation.-6: Numerical Differentiation and Integration.-7: Ordinary Differential Equations.-8: Partial Differential Equations.-9: Unconstrained Optimization.-10: Constrained Optimization.-11: Heuristics.-12: Basic Statistics.-13: Random Numbers and Simulation.-14: Linear Regression.-15: Time Series Analysis.-References.Table of ContentsAbout the Authors...........................................................................................................iPreface............................................................................................................................ii1. Why Kotlin?..............................................................................................................61.1. Kotlin in 2022.....................................................................................................61.2. Kotlin vs. C++....................................................................................................61.3. Kotlin vs. Python................................................................................................61.4. Kotlin in the future .............................................................................................62. Data Structures.......................................................................................................72.1. Function...........................................................................................................72.2. Polynomial ......................................................................................................73. Linear Algebra .......................................................................................................83.1. Vector and Matrix ...........................................................................................83.1.1. Vector Properties .....................................................................................83.1.2. Element-wise Operations.........................................................................83.1.3. Norm ........................................................................................................93.1.4. Inner product and angle ...........................................................................93.2. Matrix............................................................................................................103.3. Determinant, Transpose and Inverse.............................................................103.4. Diagonal Matrices and Diagonal of a Matrix................................................103.5. Eigenvalues and Eigenvectors.......................................................................103.5.1. Householder Tridiagonalization and QR Factorization Methods..........103.5.2. Transformation to Hessenberg Form (Nonsymmetric Matrices)...........104. Finding Roots of Single Variable Equations .......................................................114.1. Bracketing Methods ......................................................................................114.1.1. Bisection Method ...................................................................................114.2. Open Methods...............................................................................................114.2.1. Fixed-Point Method ...............................................................................114.2.2. Newton’s Method (Newton-Raphson Method) .....................................114.2.3. Secant Method .......................................................................................114.2.4. Brent’s Method ......................................................................................115. Finding Roots of Systems of Equations...............................................................125.1. Linear Systems of Equations.........................................................................125.2. Gauss Elimination Method............................................................................125.3. LU Factorization Methods ............................................................................125.3.1. Cholesky Factorization ..........................................................................125.4. Iterative Solution of Linear Systems.............................................................125.5. System of Nonlinear Equations.....................................................................126. Curve Fitting and Interpolation............................................................................146.1. Least-Squares Regression .............................................................................146.2. Linear Regression..........................................................................................146.3. Polynomial Regression..................................................................................146.4. Polynomial Interpolation...............................................................................146.5. Spline Interpolation .......................................................................................147. Numerical Differentiation and Integration...........................................................157.1. Numerical Differentiation .............................................................................157.2. Finite-Difference Formulas...........................................................................157.3. Newton-Cotes Formulas................................................................................157.3.1. Rectangular Rule....................................................................................157.3.2. Trapezoidal Rule....................................................................................157.3.3. Simpson’s Rules.....................................................................................157.3.4. Higher-Order Newton-Coles Formulas..................................................157.4. Romberg Integration .....................................................................................157.4.1. Gaussian Quadrature..............................................................................157.4.2. Improper Integrals..................................................................................158. Numerical Solution of Initial-Value Problems....................................................168.1. One-Step Methods.........................................................................................168.2. Euler’s Method..............................................................................................168.3. Runge-Kutta Methods...................................................................................168.4. Systems of Ordinary Differential Equations.................................................169. Numerical Solution of Partial Differential Equations..........................................179.1. Elliptic Partial Differential Equations...........................................................179.1.1. Dirichlet Problem...................................................................................179.2. Parabolic Partial Differential Equations........................................................179.2.1. Finite-Difference Method ......................................................................179.2.2. Crank-Nicolson Method.........................................................................179.3. Hyperbolic Partial Differential Equations.....................................................1710..................................................................................................................................1811..................................................................................................................................1912. Random Numbers and Simulation ....................................................................2012.1. Uniform Distribution .................................................................................2012.2. Normal Distribution...................................................................................2012.3. Exponential Distribution............................................................................2012.4. Poisson Distribution ..................................................................................2012.5. Beta Distribution........................................................................................2012.6. Gamma Distribution ..................................................................................2012.7. Multi-dimension Distribution ....................................................................2013. Unconstrainted Optimization ............................................................................2113.1. Single Variable Optimization ....................................................................2113.2. Multi Variable Optimization .....................................................................2114. Constrained Optimization .................................................................................2214.1. Linear Programming..................................................................................2214.2. Quadratic Programming ............................................................................2214.3. Second Order Conic Programming............................................................2214.4. Sequential Quadratic Programming...........................................................2214.5. Integer Programming.................................................................................2215. Heuristic Optimization......................................................................................2315.1. Genetic Algorithm .....................................................................................2315.2. Simulated Annealing .................................................................................2316. Basic Statistics..................................................................................................2416.1. Mean, Variance and Covariance................................................................2416.2. Moment......................................................................................................2416.3. Rank...........................................................................................................2417. Linear Regression .............................................................................................2517.1. Least-Squares Regression..........................................................................2517.2. General Linear Least Squares....................................................................2518. Time Series Analysis ........................................................................................2618.1. Univariate Time Series..............................................................................2618.2. Multivariate Time Series ...........................................................................2618.3. ARMA .......................................................................................................2618.4. GARCH .....................................................................................................2618.5. Cointegration .............................................................................................2619. Bibliography .....................................................................................................2720. Index .....................................................................................................
Beginning Spring Data
Use the popular Spring Data project for data access and persistence using various Java-based APIs such as JDBC, JPA, MongoDB, and more.This book shows how to easily incorporate data persistence and accessibility into your microservices, cloud-native applications, and monolithic enterprise applications. It also teaches you how to perform unit and performance testing of a component that accesses a database. And it walks you through an example of each type of SQL and NoSQL database covered.After reading this book, you’ll be able to create an application that interacts with one or multiple types of databases, and conduct unit and performance testing to analyze possible problems. Source code is available on GitHub.WHAT YOU’LL LEARN* Become familiar with the Spring Data project and its modules for data access and persistence* Explore various SQL and NoSQL persistence types* Uncover the persistence and domain models, and handle transaction management for SQL* Migrate database changes and versioning for SQL* Dive into NoSQL persistence with Redis, MongoDB, Neo4j, and Cassandra* Handle reactive database programming and access with R2DBC and MongoDB* Conduct unit, integration, and performance testing, and moreWHO THIS BOOK IS FORExperienced Java software application developers; programmers with experience using the Spring framework or the Spring Boot micro frameworkANDRES SACCO is a Technical Lead at Prisma. He has experience using languages such as Java, PHP, and NodeJs. He also has experience using Spring. In his previous job, Andres helped find alternative ways to optimize the transference of data between microservices, which reduced the cost of infrastructure by 55%. He also has written internal courses about new technologies and articles on Medium. Andres shares his knowledge of using different types of databases, depending on the situation. He has experience with various types of testing, to search for problems in queries or repositories that access the database. Part I - IntroductionChapter 1: Architecture of the ApplicationsChapter 2: Spring Basics and BeyondChapter 3: Spring Data and Persistence TypesPart II - SQL PersistenceChapter 4: Persistence and Domain ModelChapter 5: Transaction ManagementChapter 6: Versioning or Migrate the Changes of the DatabasePart III - NO-SQL PersistenceChapter 7: Redis key/value DatabaseChapter 8: MongoDB Document DatabaseChapter 9: Neo4j Graph DatabaseChapter 10: Cassandra wide-column DatabaseChapter 11: Reactive access w/R2DBC and MongoDBChapter 12: Unit/Integration TestingChapter 13: Performance TestingChapter 14: Best PracticesPart I - IntroductionThis part or section contains all the introduction about the basics of the Spring and the architecture of theapplication to use the persistence.Chapter 1: Architecture of the applicationsChapter Goal: In this chapter, the readers will see the different ways of structuring one application and thebest practices to organize all the things related to persistence like the use of DAO (repositories on Spring).• Small history of the methods of persistence (Plain query using the class of Java, ORM)• Different types of architectureso Layerso Hexagonal or onion• Persistence design patterso DAO (Repositories in Spring)o Data Transfer Object (DTO)Chapter 2: Spring basics and beyondChapter Goal: In this chapter, the readers will see the different ways of structuring one application and thebest practices to organize all the things related to persistence like the use of DAO (repositories on Spring).• Spring’s Architecture• Dependency Injection and Inversion of Control• Basic Application SetupChapter 3: Spring Data and different types of persistenceChapter Goal: This chapter will provide a full explanation about Spring Data, how it works and what this librarydoes behind the scenes.• How the Spring Data works• How the Repositories workso Using interfaceso Defining a custom implementationPart II - SQL persistenceThis part or section contains the information about different aspects of the persistence of databases whichhave a rigid schema. Also, the readers will see different strategies of deploying the changes on the schemas.Chapter 4: Persistence and domain modelChapter Goal: In this chapter, the readers will learn the basics about persistence and how it works behind thescenes. Also, the readers will see how to create validations in the schema like the size of the column and thedifferent types of relationship between entities.• JPA configuration using annotationso Entity, Ido Types of relationshipso Pre-update, pre-persist• Ways to define the querieso Using specificationso Define SQL• How validate the schema• Types of InherenceChapter 5: Transaction managementChapter Goal: In this chapter, the readers will learn the basics of the transactions and some concepts of ACID.• Definition of ACID• Isolation Levels• Transactional levelsChapter 6: Versioning or migrate the changes of the databaseChapter Goal: In this chapter the readers will see different tools or strategies to include the changes of thedatabases, e.g use Liquibase/Flyway, running the scripts manually, or using the auto-update of the Spring.Also, this chapter will include some mechanism to move the data from one column to another using featureflags.• Mechanism to migrate the changes• Tools to versioning the changeso Liquibaseo Flyway• Using Feature Flags to new featureso What is a Feature flag?o Benefits of use this approacho Common librariesPart III - NO-SQL persistenceIn this section the idea is to cover one example of each type of the databases NO-SQL like key/value,document, graph, and wide-column database. The idea is not to cover all more than one example of a type ofdatabase because most of them have certain operations similar.Chapter 7: Redis key/value databaseChapter Goal: In this chapter, the readers will see how to run a database and save the information using aspecific key. Also, this chapter will show the readers to create a serializer to persist data that is complex andsome best practices like persist the information in async mode.The last point is how to configure the TTL in the information that the readers persist in the database.• What is Redis and which are the benefits?• Connecting with multiples Redis• Persist synchronous or asynchronous• Object Mapping and ConversionChapter 8: MongoDB Document databaseChapter Goal: In this chapter, the readers will see how to run a mongo database and how to persist theinformation with the definition of the entities using the different operations that are permitted on MongoDB.• What is a document store?• Setting up a Mongo• Access using repositories• Manage transactions in a programmatic wayChapter 9: Neo4j Graph databaseChapter Goal: In this chapter, the readers will see how to run a database and how to create different types ofqueries. Also the reader will see the different aspects of the persistence of the information and the use ofreactive approach.• Modeling the problem as a Grapho Cases of usero Benefits• Persisting the domain• Manage transactionsChapter 10: Cassandra wide-column databaseChapter Goal: In this chapter, the readers will see how to configure the database on Spring and thedeclaration of the entities that need to be used to persist the information. Also, the different ways topersist or modify the information on Cassandra.The last point is how to configure the TTL in the information that the readers persist in the database.• What is Cassandra and how works?• Configuration for Cassandra• Access using repositories• Defining a TTLPart IV – Advanced, testing and best practicesThis part covers some aspects of any type of database to create different types of tests and validate theperformance of the queries. Also, this section covers some best practices to reduce the possible problems ormistakes in the applications that access a database.Chapter 11: Reactive accessChapter Goal: This chapter needs to cover how you can access and obtain the information in a reactive way.• What is reactive access?• Modifying queries to be reactiveo R2DBCo MongoDBChapter 12: Unit/Integration testingChapter Goal: This chapter needs to cover more in detail how you can write unit tests without using anexistent database but using the same motor of the database, to do this the reader will use Test Cointainerswith Junit 5 which is the standard to write unit tests.• Unit Testing with Mocks• Integration Testing with a Databaseo What is Test containers?o Test Containers vs embeddedo How you can use it?o Possible problems in the pipelineChapter 13: Performance testingChapter Goal: In this chapter the reader will use some tools like Gatling or QuickPerform to see how tocreate a performance test and analyze if the queries have some issue related with the use ofCPU/memory.• How check or analyze the performance of the queries?• Analyzing the complexity of queries• Performance test of an endpoint that access to a DBChapter 14: Best practicesChapter Goal: In this chapter the reader will know some strategies to improve the performance of thedatabase including some mechanism of cache to reduce the number of times that anyone accesses toobtain information.• Access to the information◦ Master-slave• Using cache to reduce the accessed to DB• Compress the information• Lazy Loading Issues• Pagination and ways to reduce the response
PHP 8 Basics
Take advantage of PHP 8's powerful features to create basic web applications, solve code tests (required for most job interviews nowadays), and begin moving towards more advanced PHP concepts. This book provides an introduction to PHP 8, including modules, attributes, JIT compiler, and union types, as well as related frameworks such as Symfony.You will explore fundamental PHP concepts through both practical and hands-on examples. You'll not only gain a solid understanding of PHP fundamentals, but will also be prepared to handle new concepts and technologies as they emerge.After working through the book and its associated demo code, you will be able to build your first basic web application.WHAT YOU WILL LEARN* Develop web applications with PHP 8* Use Vagrant, Docker, JSON API and more* Work with data, form data, arrays, objections, exceptions, regex, and more* Utilize PHP frameworks like Laravel and SymfonyWHO THIS BOOK IS FORThose new to PHP 8 or PHP in general. Some prior experience in web development and DB handling is recommended.GUNNARD ENGEBRETH began coding at the age of 11 through a “Learning BASIC” book given to him by his father. Technology was changing fast and Gunnard rode the wave from 1200 to 56k baud modems. Logging in to BBSs, Prodigy, Compuserve, Delphi and IRC he could see the world changing and he wanted to be a part of it. He soon got involved in the ansi/demo scene, making several application generators for many groups in the 90’s. Visual Basic was the next language of choice allowing him to develop “tools” for online systems such as AOL. This introduced many aspects of development, security and UI while they were still in their infancy. Once the WWW arrived via Mindspring in Atlanta, Ga. Gunnard quickly joined in the race for the web. Learning HTML, PERL and Linux (Slackware at the time) he began to build his skill-set which lead to a full-time Sysadmin position at the age of 20 (2000) at Activegrams/Silverpop. Gunnard has moved around the IT industry from SAN/NAS storage at IBM to custom Wordpress sites for marketing companies, but one thing has stayed the same, a passion for learning and problem solving. Gunnard also DJ’s Drum and Bass as Section31, Playing drums and baking bread.SATEJ KUMAR SAHU works in the role of Senior Enterprise Architect at Honeywell. He is passionate about technology, people, and nature. He believes through technology and conscientious decision making, each of us has the power to make this world a better place. In his free time, he can be found reading books, playing basketball, and having fun with friends and family.Chapter 1: Getting StartedChapter 2: PHP FundimentalsChapter 3: Functions and ClassesChapter 4: DataChapter 5: Form dataChapter 6: ArraysChapter 7: Cookies and SessionsChapter 8: ObjectsChapter 9: Exceptions, Validation, Regular expressionsChapter 10: PHP & MySQL working togetherChapter 11: Basic Database DesignChapter 12: Creating a DB with PHP and MYsqlChapter 13: Basic Website with DBChapter 14: Basic JSON APIChapter 15: Intro to PHP FrameworksChapter 16: Intro to LaravelChapter 17: Intro to SymfonyChapter 18: Basic Symfony applicationChapter 19: Symfony Json APIChapter 20: Intro to Zend / Laminas ProjectChapter 21: Basic Zend / Laminas Project applicationChapter 22: Zend / Laminas Project JSON APIChapter 23: Intro to Slim PHPChapter 24: Basic Slim PHP applicationChapter 25: Slim PHP JSON APIChapter 26 or appendix: Wordpress developmentChapter 27 or appendix: Shopify development
Introducing ReScript
This book serves as a succinct guide on ReScript, a functional language for building web applications. Using examples of ReScript language features along with explanations of fundamental concepts in functional programming, this book will show web developers with a background in JavaScript how to effectively use ReScript to its full potential.In Introducing ReScript, you'll learn how to use features in ReScript that JavaScript lacks, such as type inference, null-safety, algebraic data types, pattern matching, and more. Along the way, you'll pick up functional programming concepts like immutability and higher-order functions. You'll also gain a sense of how ReScript works under the hood and how to leverage interoperability between ReScript and JavaScript.Whether you're a web developer interested in dabbling with functional programming or you just want to learn how to write safer and cleaner code for web applications, this book is a great way for you to get started with ReScript.WHAT YOU WILL LEARN* Use ReScript to write clean, safe, and elegant software* Understand the features of ReScript that set it apart from JavaScript, such as type inference, null-safety, and algebraic data types* Explore functional programming concepts like immutabhigher-orderr order functions, and pattern matching* Use popular JavaScript libraries and frameworks in your ReScript code and integrate ReScript code into JavaScript codebasesWHO THIS BOOK IS FORWeb developers that want a strictly typed, safer alternative to JavaScript, as well as web developers interested in learning functional programming and leveraging the elegant and powerful functional features in ReScript.Danny Yang is a professional software engineer at Meta working on infrastructure for WhatsApp. He has previously worked on Facebook Messenger, including the web interface which was written in ReScript. His technical interests include functional programming, compilers, and data visualization, which he writes about on his blog.Chapter 1, IntroChapter Goal: Learn what functional programming is, and the background of the ReScript language● What is ReScript?● Why should you learn ReScript?● What is functional programming?● Why should you learn functional programming?Chapter 2, BasicsChapter Goal: Learn the basic features of ReScript, like expressions and operators- Development environment setup- Hello, World in ReScript- Expressions- Operators- If expressions- Let expressions- Printing and debuggingChapter 3, FunctionsChapter Goal: learn how functions work in ReScript- Defining a function- Applying a function- Polymorphic functions- Anonymous functionsChapter 4, Lists and ArraysChapter Goal: learn the data structures for ordered data in ReScript, learn about immutable data structures- Building a list- Accessing a list- Mutating a list- Arrays and mutability- IterationChapter 5, Records and ObjectsChapter Goal: learn the ways to represent composite data types in ReScript- Records- ObjectsChapter 6, Pattern Matching and DestructuringChapter Goal: learn one of ReScript's most powerful features and how to work with the shape of your data- Pattern matching/switch- Destructuring with let- Destructuring in functionsChapter 7, Algebraic Data TypesChapter Goal: learn how represent complex data in ReScript's type system- Variants- Polymorphic Variants- Options- TuplesChapter 8, Higher Order ProgrammingChapter Goal:- Higher order functions- Map- Filter- Reduce- Generalizing to other data structures- Piping- CurryingChapter 9, ModulesChapter Goal: Introduce modules in ReScript, and how they can be used for higher order programming- What are modules- Scope/visibility- Signature- Import/Export- FunctorsChapter 10, Using ReScript in ProductionChapter Goal: learn about ReScript's interoperability with JavaScript- Calling ReScript from JavaScript- Calling JavaScript from ReScript- Embedding JavaScript in ReScript- Working with DOM- Working with JSON- Runtime representation
Productionizing AI
This book is a guide to productionizing AI solutions using best-of-breed cloud services with workarounds to lower costs. Supplemented with step-by-step instructions covering data import through wrangling to partitioning and modeling through to inference and deployment, and augmented with plenty of Python code samples, the book has been written to accelerate the process of moving from script or notebook to app.From an initial look at the context and ecosystem of AI solutions today, the book drills down from high-level business needs into best practices, working with stakeholders, and agile team collaboration. From there you’ll explore data pipeline orchestration, machine and deep learning, including working with and finding shortcuts using artificial neural networks such as AutoML and AutoAI. You’ll also learn about the increasing use of NoLo UIs through AI application development, industry case studies, and finally a practical guide to deploying containerized AI solutions.The book is intended for those whose role demands overcoming budgetary barriers or constraints in accessing cloud credits to undertake the often difficult process of developing and deploying an AI solution.WHAT YOU WILL LEARN* Develop and deliver production-grade AI in one month* Deploy AI solutions at a low cost* Work around Big Tech dominance and develop MVPs on the cheap* Create demo-ready solutions without overly complex python scripts/notebooksWHO THIS BOOK IS FOR:Data scientists and AI consultants with programming skills in Python and driven to succeed in AI.BARRY WALSH is a software-delivery consultant and AI trainer at Pairview with a background in exploiting complex business data to optimize and de-risk energy assets at ABB/Ventyx, Infosys, E.ON, Centrica, and his own start-up ce.tech. He has a proven track record of providing consultancy services in Data Science, BI, and Business Analysis to businesses in Energy, IT, FinTech, Telco, Retail, and Healthcare, Barry has been at the apex of analytics and AI solutions delivery for 20 years. Besides being passionate about Enterprise AI, Barry spends his spare time with his wife and 8-year-old son, playing the piano, riding long bike rides (and a marathon on a broken toe this year), eating out whenever possible or getting his daily coffee fix.Chapter 1: Introduction to AI & the AI EcosystemChapter Goal: Embracing the hype and the pitfalls, introduces the reader to current and emerging trends in AI and how many businesses and organisations are struggling to get machine and deep learning operationalizedNo of pages: 30Sub -Topics1. The AI ecosystem2. Applications of AI3. AI pipelines4. Machine learning5. Neural networks & deep learning6. Productionizing AIChapter 2: AI Best Practise & DataOpsChapter Goal: Help the reader understand the wider context for AI, key stakeholders, the importance of collaboration, adaptability and re-use as well as DataOps best practice in delivering high-performance solutionsNo of pages: 20Sub - Topics1. Introduction to DataOps and MLOps2. Agile development3. Collaboration and adaptability4. Code repositories5. Module 4: Data pipeline orchestration6. CI / CD7. Testing, performance evaluation & monitoringChapter 3: Data Ingestion for AIChapter Goal: Inform on best practice and the right (cloud) data architectures and orchestration requirements to ensure the successful delivery of an AI project.No of pages : 20Sub - Topics: 1. Introduction to data ingestion2. Data stores for AI3. Data lakes, warehousing & streaming4. Data pipeline orchestrationChapter 4: Machine Learning on CloudChapter Goal: Top-down ML model building from design thinking, through high level process, data wrangling, unsupervised clustering techniques, supervised classification, regression and time series approaches before interpreting results and algorithmic performanceNo of pages: 20Sub - Topics:1. ML fundamentals2. EDA & data wrangling3. Supervised & unsupervised machine learning4. Python Implementation5. Unsupervised clustering, pattern & anomaly detection6. Supervised classification & regression case studies: churn & retention modelling, risk engines, social media sentiment analysis7. Time series forecasting and comparison with fbprophetChapter 5: Neural Networks and Deep LearningChapter Goal: Help the reader establish the right artificial neural network architecture, data orchestration and infrastructure for deep learning with TensorFlow, Keras and PyTorch on CloudNo of pages: 40Sub - Topics:1. An introduction to deep learning2. Stochastic processes for deep learning3. Artificial neural networks4. Deep learning tools & frameworks5. Implementing a deep learning model6. Tuning a deep learning model7. Advanced topics in deep learningChapter 6: The Employer’s Dream: AutoML, AutoAI and the rise of NoLo UIsChapter Goal: Building on acquired ML and DL skills, learn to leverage the growing ecosystem of AutoML, AutoAI and No/Low code user interfacesNo of pages: 20Sub - Topics:1. AutoML2. Optimizing the AI pipeline3. Python-based libraries for automation4. Case Studies in Insurance, HR, FinTech & Trading, Cybersecurity and Healthcare5. Tools for AutoAI: IBM Cloud Pak for Data, Azure Machine Learning, Google Teachable MachinesChapter 7: AI Full Stack: Application DevelopmentChapter Goal: Starting from key business/organizational needs for AI, identify the correct solution and technologies to develop and deliver “Full Stack AI”No of pages: 20Sub - Topics:6. Introduction to AI application development7. Software for AI development8. Key Business applications of AI:• ML Apps• NLP Apps• DL Apps4. Designing & building an AI applicationChapter 8: AI Case StudiesChapter Goal: A comprehensive (multi-sector, multi-functional) look at the main AI use uses in 2022No of pages: 20Sub - Topics:1. Industry case studies2. Telco solutions3. Retail solutions4. Banking & financial services / fintech solutions5. Oil & gas / energy & utilities solutions6. Supply chain solutions7. HR solutions8. Healthcare solutions9. Other case studiesChapter 9: Deploying an AI Solution (Productionizing & Containerization)Chapter Goal: A practical look at “joining the dots” with full-stack deployment of Enterprise AI on CloudNo of pages: 20Sub - Topics:1. Productionizing an AI application2. AutoML / AutoML3. Storage & Compute4. Containerization5. The final frontier…
Practical Spring Cloud Function
Unlike other resources that target only programming communities, this book targets both programming and business communities. With programming models shifting more towards no-code and low-code, citizen programmers from the business side will welcome this book as a guide for how to design and optimize their information pipeline while lowering costs for infrastructure. Programmers, on the other hand, will welcome this book's business-centric programming view, which will get them a step closer to fulfilling real business requirements.Practical Spring Cloud Function touches on the themes of portability, scalability, high performance and high availability. Each theme is explored via a real enterprise use case and code. The use cases target industries including energy (oil pipeline sensors), automotive (event-driven connected vehicles), and retail (conversational AI).After reading this book, you'll come away with the know-how to build and deploy cloud-native Java applications effectively and efficiently.WHAT YOU WILL LEARN* Write functions and deploy to Amazon Web Services, Microsoft Azure, Google Cloud, IBM Cloud, and on-prem clouds such as VMWare Tanzu and RedHat OpenShift* Set up locally with KNative on Kubernetes, as well as on AWS, Azure, GCP, Tanzu, and others* Build, test, and deploy a simple example with Spring Cloud Function* Develop an event-driven data pipeline with Spring Cloud Function* Integrate with AI and machine learning models* Apply Spring Cloud Function to the Internet of Things (IoT)* Get industry-specific examples of Spring Cloud Function in actionWHO THIS BOOK IS FORSoftware and cloud-native application developers with prior programming experience in the cloud and/or Spring Framework. DevOps professionals may find this book beneficial as well.Banu Parasuraman is a Cloud Native Technologist with over 30 years of experience in the IT industry. He provides an advisory role to clients who are looking to move to cloud or implement cloud-native platforms such as Kubernetes, Cloud Foundry and the like. He has engaged over 25 select companies spread across different sectors (Retail, Healthcare, Logistics, Banking, Manufacturing, Automotive, Oil & Gas, Pharmaceuticals, Media & Entertainment ...) in USA, Europe and Asia have interacted at every level of an organization. Banu is a key evangelist for Cloud-Native computing encouraging client and architects to undertake this journey as soon as possible to avoid organizational inertia later. He is experienced in most of the popular cloud platforms such as VMWare-VCF, Pivotal-PCF, IBM-OCP, Google-GCP, Amazon-AWS, Microsoft-Azure. Banu has taken part in external speaking engagements targeted at CXOs and Engineers: VMworld, SpringOne, Spring Days, Spring Developer Forum Meetups. Internal speaking engagements: Developer Workshops on Cloud Native Architecture and Development, Customer Workshops on Pivotal Cloud Foundry, enabling Cloud Native sales plays and strategies for sales and teams. Lastly, Banu has numerous blogs on platforms such a Medium and Linkedin to promote adoption of Cloud Native architecture and development.1. Why Spring Cloud FunctionsThis chapter takes the reader through the need for Spring Cloud Functions and KNative. The rationale for Spring Cloud Functions will be elucidated through example implementation on on-prem and cloud infrastructures. The chapter highlights the “code once deploy anywhere” characteristic of Spring Cloud Functions.Subtitles1. Writing functions and deploying to any hyperscaler2. Example code3. Spring Cloud Functions on AWS (EKS, Fargate)4. Spring Cloud Functions on Azure (AKS)5. Spring Cloud Functions on Google (Cloud Run)6. Spring Cloud Functions on VMWare Tanzu (TKG, PKS)7. Spring Cloud Functions on RedHat OpenShift (OCP)2. Getting Started with Spring Cloud FunctionsThis chapter walks the reader through the steps required to get started with Spring Serverless on their platform of choice, either locally, on-prem or on the cloud. Step by Step instructions take the reader through the process of getting the environment set up for coding.Subtitles1. Step by Step: Setup locally with Kubernetes and KNative with Spring Cloud Functions2. Step by Step: Setup on AWS with EKS and KNative with Spring Cloud Functions3. Step by Step: Setup on GCP with Cloud Run/GKE and KNative with Spring Cloud Functions4. Step by Step: Setup on Azure with AKS and KNative with Spring Cloud Functions5. Step by Step: Setup on VMWare Tanzu TKG and KNative6. Step by Step: Setup on RedHat Openshift and KNative3. Coding, testing, and deploying with Spring Cloud FunctionsThis chapter covers the coding, testing, and deploying using your favorite IDE like Eclipse, Eclipse Che, Intelij IDEA, Redhat Code Ready Workspace. The reader will build an example and deploy to their favorite platforma. Building a simple example with Spring Cloud Functionsb. Testing the example will sample datac. Setting up a CI/CD pipeline for deploying to a target platformd. Deploying to the target platfomi. AWSii. GCPiii. Azureiv. VMWare Tanzuv. RedHat Openshift4. Building Event Driven Data pipelines with Spring Cloud FunctionsEvent Driven data pipelines act as a conduit to flow of data based on a specific event. The event can be a purchase order triggered on the website that initiate a data flow chain that includes aggregation of data from various data sources and splitting the data to various consumers. This chapter will discuss the various ways that Spring Spring Serverless can be implemented in the various Cloud providersSubtitles1. Spring Cloud Functions and Spring Cloud Data Flow and Spring Cloud Streams2. Spring Cloud Functions and AWS Glue3. Spring Cloud Functions and Google Cloud Data Flow4. Spring Cloud Functions and Azure Data Factory5. AI/ML Trained Serverless Endpoints with Spring Cloud FunctionsConversational AI models are one of the complex implementations that may lead to heavy use of resources in the cloud. Leveraging Serverless infra and functions can help alleviate the costs by being invoked only when needed. This chapter will help layout the blueprint of how to leverage Spring Serverless with on-prem or cloud-based AI/ML environmentsSubtitles1. Spring Cloud Functions with Google Cloud Functions and Tensor Flow2. Spring Cloud Functions with AWS Glue and AWS Sage or AI/ML3. Spring Cloud Functions with Azure Data Factory and Azure ML4. Spring Cloud Functions with Apache AI/ML on-prem VMWare Tanzu and Openshift6. Spring Cloud Functions and IOTThis chapter will take the reader through blueprints and architect diagrams of how Spring serverless works in conjunction with IOT on various Hyperscalers (Cloud Providers) or SaaS IOT Gateway providers.Subtitles1. Spring Cloud Functions on the Cloud with AWS IOT2. Spring Cloud Functions on the cloud with Azure IOT3. Spring Cloud Functions on the cloud with GCP IOT4. Spring Cloud Functions on-prem with IOT gateway on a SaaS provider (Eg, SmartSense)7. Industry specific examples with Spring Cloud FunctionsThis chapter will provide industry specific examples and use cases that will help the reader understand how Spring Serverless can be leveraged within their specific business use case1. Oil/ Natural gas pipeline tracking with Spring Cloud Functions, IOT and Spring Cloud Data Flow2. Enabling ubiquitous health care with Spring Cloud Functions and Big Data Pipelines3. Connected vehicles with Spring Cloud Functions4. Conversational AI in Retail with Spring Cloud Functions
Kubernetes Programming with Go
This book begins by introducing the structure of the Kubernetes API and which operations it serves. Following chapters demonstrate how to write native Kubernetes resources definitions using Go structures defined in the API and API Machinery libraries. Miscellaneous utilities are described to help you work with different resource fields and to convert your resource definitions to or from YAML or JSON. Next, you will learn how to interact with the Kubernetes API server to create, delete, update, and monitor resources in a cluster using the client-go library. A complete chapter is devoted to tools provided to test your programs using the client-go library. An example follows to wrap up the first part of the book, describing how to write a kubectl plugin. Next, you will learn how to extend the Kubernetes API using Custom Resource Definitions, and how to write Kubernetes resources in a generic way as well as how to create your own resources using the unstructured concept. The next chapters delve into the controller-runtime library, useful for extending Kubernetes by writing operators, and the kubebuilder framework, which leverages this library, to help you start writing operators in minutes.After reading this book, you will have a deep understanding of the Kubernetes API’s structure and how Kubernetes resources are organized within it, and have at your disposal a complete toolbox to help you write Kubernetes clients and operators.WHAT YOU WILL LEARN* Understand how the Kubernetes API and its resources are organized* Write Kubernetes resources in Go* Create resources in a cluster* Leverage your newly-gained knowledge to write Kubernetes clients and operatorsWHO IS THIS BOOK FOR:Software engineers and (Site Reliability Engineers) SREs wishing to write Kubernetes clients and operators using the Go language.Philippe Martin has been working with Kubernetes for five years, first by creating an operator to deploy video CDNs into the cloud, later helping companies deploy their applications into Kubernetes, then writing a client to help developers work in a Kubernetes environment. Philippe passed the CKAD, CKA and CKS certifications.He has long experience with distributed systems and open-source software: he started his career 20 years ago creating thin clients based on the Linux kernel and open source components. He is currently working at Red Hat on the Development Tools team.Philippe is active in the development of Kubernetes, especially its documentation, and participates in the translation of the official documentation into French, has edited two reference books about the Kubernetes API and kubectl, and is responsible for the French translation of the Kubernetes Dashboard. He participated in Google Season of Docs to create the new Kubernetes API Reference section of the official documentation, and is maintaining it. He is currently participating in the Apps SIG, a group that covers deploying and operating applications in Kubernetes.Chapter 1: Kubernetes API Introduction.Chapter 2: Kubernetes API Operations.Chapter 3: Working with API Resources in Go.Chapter 4: Using Common types.Chapter 5: The API Machinery.Chapter 6: The Client-go library.Chapter 7: Testing Applications using Client-Go.Chapter 8: Extending Kubernetes API with Custom Resources Definitions.Chapter 9: Working with Custom Resources.Chapter 10: Writing Operators with the controller-runtime Library.Chapter 11: Writing the Reconcile Loop.Chapter 12: Testing the Reconcile Loop.Chapter 13: Creating an Operator with Kubebuilder.
Pro Android with Kotlin
Develop Android apps with Kotlin to create more elegant programs than the Java equivalent. This revised book covers the various aspects of a modern Android app that professionals are expected to encounter. You'll use the latest Kotlin APIs as made available in most recent versions of the Android SDK.There are chapters dealing with all the important aspects of the Android platform, including GUI design, file- and data-handling, coping with phone calls, multimedia apps, interaction with location and mapping services, monetizing apps, and much more. Jetpack will also be covered. It is a suite of libraries to help developers follow best practices, reduce boilerplate code, and write code that works consistently across Android versions and devices.Pro Android with Kotlin, Second Edition is an invaluable source for developers wanting to build real-world, state-of-the-art Android apps for modern Android devices using the Kotlin programming language and its APIs as available in the modern Android SDK. After reading this book, you'll come away with the skills and techniques to build modern Android apps that you can sell on Google Play. Free source code is available on this book's Github page as well.WHAT YOU WILL LEARN* Integrate activities, such as intents, services, notifications and more, into your Android apps* Build UIs in Android using layouts, widgets, lists, menus, and action bars* Deal with data in your Android apps using data persistence and cloud access* Design for different Android devices* Create multimedia apps in Android* Secure, deploy, and monetize your Android appsWHO THIS BOOK IS FORProfessional Android app developers.PETER SPÄTH graduated in 2002 as a physicist and soon afterward became an IT consultant, mainly for Java related projects. In 2016 he decided to concentrate on writing books on various subjects, with a primary focus on software development. With a wealth of experience in Java-related languages, the release of Kotlin for building Android Apps made him enthusiastic about writing books for Kotlin development in the Android environment. 1. System.- 2. Application.- 3. Activities.- 4. Services.- 5. Broadcasts 6. Content Providers.- 7. Permissions.- 8. APIs.- 9. User Interface.- 10. Development.- 11. Building.- 12. Communication.- 13. Hardware.- 14. Testing.- 15. Troubleshooting.- 16. Distributing Apps.- 17. Instant Apps.- 18. CLI.
Time Series Algorithms Recipes
This book teaches the practical implementation of various concepts for time series analysis and modeling with Python through problem-solution-style recipes, starting with data reading and preprocessing.It begins with the fundamentals of time series forecasting using statistical modeling methods like AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average), and ARIMA (autoregressive integrated moving-average). Next, you'll learn univariate and multivariate modeling using different open-sourced packages like Fbprohet, stats model, and sklearn. You'll also gain insight into classic machine learning-based regression models like randomForest, Xgboost, and LightGBM for forecasting problems. The book concludes by demonstrating the implementation of deep learning models (LSTMs and ANN) for time series forecasting. Each chapter includes several code examples and illustrations.After finishing this book, you will have a foundational understanding of various concepts relating to time series and its implementation in Python.WHAT YOU WILL LEARN* Implement various techniques in time series analysis using Python.* Utilize statistical modeling methods such as AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average) and ARIMA (autoregressive integrated moving-average) for time series forecasting * Understand univariate and multivariate modeling for time series forecasting* Forecast using machine learning and deep learning techniques such as GBM and LSTM (long short-term memory)WHO THIS BOOK IS FORData Scientists, Machine Learning Engineers, and software developers interested in time series analysis.AKSHAY KULKARNI IS an AI and machine learning (ML) evangelist and a thought leader. He has consulted several Fortune 500 and global enterprises to drive AI and data science-led strategic transformations. He has been honoured as Google Developer Expert, and is an Author and a regular speaker at top AI and data science conferences (including Strata, O’Reilly AI Conf, and GIDS). He is a visiting faculty member for some of the top graduate institutes in India. In 2019, he has been also featured as one of the top 40 under 40 Data Scientists in India. In his spare time, he enjoys reading, writing, coding, and helping aspiring data scientists. He lives in Bangalore with his family.ADARSHA SHIVANANDA IS a Data science and MLOps Leader. He is working on creating worldclass MLOps capabilities to ensure continuous value delivery from AI. He aims to build a pool of exceptional data scientists within and outside of the organization to solve problems through training programs, and always wants to stay ahead of the curve. He has worked extensively in the pharma, healthcare, CPG, retail, and marketing domains. He lives in Bangalore and loves to read and teach data science.ANOOSH KULKARNI is a data scientist and a Senior AI consultant. He has worked with global clients across multiple domains and helped them solve their business problems using machine learning (ML), natural language processing (NLP), and deep learning.. Anoosh is passionate about guiding and mentoring people in their data science journey. He leads data science/machine learning meet-ups and helps aspiring data scientists navigate their careers. He also conducts ML/AI workshops at universities and is actively involved in conducting webinars, talks, and sessions on AI and data science. He lives in Bangalore with his family.V ADITHYA KRISHNAN is a data scientist and ML Ops Engineer. He has worked with various global clients across multiple domains and helped them to solve their business problems extensively using advanced Machine learning (ML) applications. He has experience across multiple fields of AI-ML, including, Time-series forecasting, Deep Learning, NLP, ML Operations, Image processing, and data analytics. Presently, he is working on a state-of-the-art value observability suite for models in production, which includes continuous model and data monitoring along with the business value realized. He also published a paper at an IEEE conference, “Deep Learning Based Approach for Range Estimation," written in collaboration with the DRDO. He lives in Chennai with his family.Chapter 1: Getting Started with Time Series.Chapter Goal: Exploring and analyzing the timeseries data, and preprocessing it, which includes feature engineering for model building.No of pages: 25Sub - Topics1 Reading time series data2 Data cleaning3 EDA4 Trend5 Noise6 Seasonality7 Cyclicity8 Feature Engineering9 StationarityChapter 2: Statistical Univariate ModellingChapter Goal: The fundamentals of time series forecasting with the use of statistical modelling methods like AR, MA, ARMA, ARIMA, etc.No of pages: 25Sub - Topics1 AR2 MA3 ARMA4 ARIMA5 SARIMA6 AUTO ARIMA7 FBProphetChapter 3: Statistical Multivariate ModellingChapter Goal: implementing multivariate modelling techniques like HoltsWinter and SARIMAX.No of pages: 25Sub - Topics: 1 HoltsWinter2 ARIMAX3 SARIMAXChapter 4: Machine Learning Regression-Based Forecasting.Chapter Goal: Building and comparing multiple classical ML Regression algorithms for timeseries forecasting.No of pages: 25Sub - Topics:1 Random Forest2 Decision Tree3 Light GBM4 XGBoost5 SVMChapter 5: Forecasting Using Deep Learning.Chapter Goal: Implementing advanced concepts like deep learning for time series forecasting from scratch.No of pages: 25Sub - Topics:1 LSTM2 ANN3 MLP
Beginning Cloud Native Development with MicroProfile, Jakarta EE, and Kubernetes
Get ready to develop microservices using open source Eclipse MicroProfile and Jakarta EE, and deploy them on Kubernetes/Docker. This book covers best practices for developing cloud-native applications with MicroProfile and Jakarta EE.This book introduces you to cloud-native applications and teaches you how to set up your development environment. You'll learn about the various components of MicroProfile, such as fault tolerance, config, health check, metrics, and JWT auth. You'll develop a RESTful web service made up of some microservices. You'll deploy your application on Docker and Kubernetes.After reading this book, you'll come away with the fundamentals you need to build and deploy your first cloud-native Java-based app.WHAT YOU'LL LEARN* Build your first cloud-native Java-based app with the open source MicroProfile platform, and Jakarta EE 10 APIs * Develop a RESTful web service using MicroProfile and Jakarta EE* Discover and explore the key components of the MicroProfile framework, such as config, metrics, health, JWT authentication, and more* Deploy your cloud-native application on the Kubernetes container orchestration platform* Get up to speed with other popular technologies such as Docker containers, Kubernetes clusters, and ZipkinWHO THIS BOOK IS FORProgrammers with at least some prior experience in Java programming who may be new to MicroProfile and Jakarta EE. Some prior experience with Java-based microservices and web development is recommended, but not required.TARUN TELANG is a hands-on technologist with extensive experience in architecture and implementing multi-tiered, highly scalable software applications. He has more than 17 years of expertise developing software applications for well-known companies such as Microsoft, Oracle, and SAP.In 2005, Tarun worked on configuration and management in several enterprise solutions for SAP using the Java Management Extensions (JMX) technology. He also gained expertise in various integration technologies, such as SOAP, XML, and JSON, and used them to develop solutions to handle message-oriented communications across numerous systems. In 2007, Tarun was named SAP Mentor and Community Influencer for his articles and blog posts on emerging technologies and for promoting innovative solutions in the SAP Developer Community.Tarun has the following certifications: Oracle Certified Programmer for Java 6.0 Platform, SAP Certified Development Consultant for NetWeaver 04 Java Web Application Development, SAP Certified Application Management Expert for End-to-End Root Cause Analysis - Solution Manager 4.0, and NASBA Certification on Remote Work.Tarun is an expert in web, mobile, and cloud technologies. He has developed many end-to-end cloud-based solutions using various architectural patterns, including Microservices, RESTful web services, and Service Oriented Architecture.For more than 15 years, Tarun has been actively publishing technical articles and blogs on various software technologies. He frequently writes articles on Java and related technologies. He has also authored multiple books on Java and Jakarta EE 10.Having worked in Canada and Germany, Tarun currently resides in Hyderabad, India, with his wife and child. You can follow him on Twitter at @taruntelang or visit his LinkedIn Profile.Tarun loves mentoring software professionals and programmers, and teaching them about current industry trends and best practices. His blogs at blogs.taruntelang.me are excellent resources for everything related to Java technology.1. Introduction to Cloud-Native Applications1.1. What are Cloud-Native Applications?1.2. Why Use Cloud-Native Applications?1.3. What are the Benefits of Using Cloud-Native Applications?2. Setting Up Your Development Environment2.1. Prerequisites2.2. Installing Java SE 172.3. Installing Kubernetes2.4. Installing Docker3. Creating a Config Component3.1. What is a Config Component?3.2. Setting Up the Config Component3.3. Accessing the Configuration Data in Your Application4. Using the Fault Tolerance Component4.1. What is the Fault Tolerance Component?4.2. Configuring the Fault Tolerance Component4.3. Handling Failures in Your Application5. Using the Health Check Component5.1. What is the Health Check Component?5.2. Configuring the Health Check Component5.3. Checking the Health of Your Application6. Using the Metrics Component6.1. What is the Metrics Component?6.2. Collecting Metrics Data in Your Application7. Using the JWT Authentication Component7.1. What is the JWT Authentication Component?7.2. Configuring the JWT Authentication Component7.3. Authenticating Users in Your Application8. Developing a RESTful Web Service8.1. What is a RESTful Web Service?8.2. Developing a RESTful Web Service8.3. Implementing the HTTP Methods9. Deploying an Application on Kubernetes/Docker9.1. What is Kubernetes?9.2. What is Docker?9.3. Installing Kubernetes9.4. Creating a Kubernetes Cluster9.5. Installing Docker on Kubernetes9.6. Deploying an Application on Kubernetes/Docker9.7. Benefits of using Jakarta EE and Kubernetes/Docker for developing cloud-native applications.
Exploring Blazor
Build and develop web applications with Blazor in C#. This book covers both server-side and client-side Blazor, along with its latest features and the structure of the technology. You’ll see that Blazor is a web UI framework based on C#, Razor, and HTML, and how it runs front-end logic using C#, either on the server or on the browser, using WebAssembly.This new edition not only covers the new structure for the Blazor environment, it also demonstrates the latest features, such as adding API features to a Blazor server project; creating code-behind files for C# and CSS; new ways to pick, save, and handle files in Blazor; and much more. The code and project layout have been updated in .NET 7 for this new edition.The book starts with an introduction to Blazor, along with its various categories and its basics and syntax, including Razor syntax implementation. You will go through Blazor navigation and components, and learn its life cycle events and other components. You will learn features specific to each Blazor type. You will see how Blazor works with storage, files, and JavaScript, and you will create a Blazor code library. You will also create web applications in Blazor using practical implementations and real-life scenarios for both the server side and the client side.After reading this book, you will be able to build web applications with Blazor in C#11 and .NET Core 7.0.WHAT YOU WILL LEARN* Bind data and handle events in C# Blazor* Handle components and page navigation in Blazor* Connect Blazor front-end to APIs* Interact with files using Blazor* Understand the layout of Visual Studio Blazor project templates WHO THIS BOOK IS FORC# and .NET Core developers.TAURIUS LITVINAVICIUS is a businessman and technology expert based in Lithuania who has worked with organizations in building and implementing various projects in software development, sales, and other fields of business. He currently works on modern financial applications and consults companies on technology and cost-related issues. As with most of his projects, this book uses cutting-edge technologies, such as Blazor. Taurius is responsible for technological improvements, development of new features, and general management.CHAPTER 1 – INTRODUCTION1. What is Blazor2. Blazor typesCHAPTER 2 – SYNTAX AND BASICS OF BLAZOR1. Syntax2. Binding data3. Events and event argumentsCHAPTER 3 – BLAZOR COMPONENTS AND NAVIGATION1. Pages and navigation2. Lifecycle events3. Components4. Custom events in componentsCHAPTER 4 – SPECIFICS OF DIFFERENT TYPES OF BLAZOR1. Injection (Blazor server-side)2. Static values in Blazor server-side3. Calling APIs (Blazor client-side)4. Adding API Controller (Blazor server-side)5. Cleaning project templates in Visual studioCHAPTER 5 – GENERAL BLAZOR1. Interact with Javascript2. Code-behind files3. Local storage4. Pick and save files5. Creating Blazor code library6. Background tasksCHAPTER 6 – PRACTICE TASKS (SERVER -SIDE BLAZOR)1. Task 12. Task 2CHAPTER 7 – PRACTICE TASKS (CLIENT -SIDE BLAZOR)3. Task 14. Task 25. Task 3
Beginner's Guide to Streamlit with Python
This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you’ll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models.Beginner's Guide to Streamlit with Python begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You’ll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you’ll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural language processing apps with computer vision implemented using Streamlit.After reading this book, you will understand the concepts, functionalities, and performance of Streamlit, and be able to develop dynamic Streamlit web-based data and machine learning applications of your own.WHAT YOU WILL LEARN* How to start developing web applications using Streamlit* What are Streamlit's components * Media elements in Streamlit* How to visualize data using various interactive and dynamic Python libraries* How to implement models in Streamlit web applicationsWHO THIS BOOK IS FORProfessionals working in data science and machine learning domains who want to showcase and deploy their work in a web application with no prior knowledge of web development. Sujay Raghavendra is an IT professional with a Master’s Degree in Information Technology. His research interests include machine learning, computer vision, NLP, and deep learning. He has been a consultant for multiple research centers in various universities. He has published many research articles in international journals and is the author of the book “Python Testing with Selenium” published by Apress. CHAPTER 1. INTRODUCTION TO STEAMLITChapter Goal: Introduce the reader to the Streamlit libraryNo of pages - 10Sub -Topics1. A brief introduction to Streamlit2. Pre-requisites and installation guide for Streamlit3. Creating our first Streamlit applicationCHAPTER 2. TEXTS & TABLE ELEMENTSChapter Goal: The text is one of the important features that will be discussed in this chapter.No of pages - 10Sub -Topics1. Write title, header, sub-header, markdown and a caption.2. Code text, latex and default text in an application.3. json, table, metric and dataframe in the application.CHAPTER 3. CHARTS / VISUALIZATIONChapter Goal: Visualization is one of the important aspects in data science and machine learning. The visualizing techniques helps to understand the data more appropriately. In this chapter, we will implement different visualizing techniques that are available in python for data science and machine learning developers.No of pages - 20Sub -Topics1. Implementing simple charts2. Visualizing data using interactive charts in the application.3. Implementing data into the maps.CHAPTER 4. DATA AND MEDIA ELEMENTSChapter Goal: In this chapter, we will learn how media elements can be used in the streamlit application.No of pages - 20Sub -Topics1. We will first try to implement simple charts to start with and display them on the application.2. Next, we will visualize data using interactive charts in the application.3. At last, we will see how we can use data into the maps.CHAPTER 5. BUTTONSChapter Goal: One more important feature from Streamlit are buttons. These buttons are used to select the required data to process or visualize in the application developed.No of pages - 20Sub -Topics1. Introduction to buttons2. Discuss various buttons like download button, checkbox, radio buttons and multiselect.3. Sliders to select specific range of data.CHAPTER 6. FORMSChapter Goal: This chapter mainly focusses on data that will be provided by the user to process data in the application. We will discuss user data in terms forms.No of pages - 20Sub -Topics1. Discuss various types input data like numbers and text.2. Discuss advanced input data like date, time, file uploads and color picker.3. Getting live image data from webcamCHAPTER 7. NAVIGATIONSChapter Goal: This chapter discusses about navigation on the application to be developed. The primary aim is to learn how to switch between multiple pages in an application using navigation.No of pages - 20Sub -Topics1. Discuss on navigation.2. Discuss the complex layouts associated with it.3. Discuss on containers that can be used to hold multiple elements in it.CHAPTER 8. CONTROL FLOW AND STATUSChapter Goal: We will discuss on custom handling of application using control flow in this chapter. We will also learn on status elements provided by streamlit.No of pages - 20Sub -Topics1. Handling functionality of the application using control flow.2. Flow control of application can be changed from its default flow.3. We will also check on the what are status elements? and their types available in Streamlit.CHAPTER 9. ADVANCED FEATURESChapter Goal: In this chapter, we will discuss on huge data handling, mutating data and optimizing performance of the Streamlit application.No of pages - 20Sub -Topics1. Handling huge data in the Streamlit Application developed for data science and machine learning.2. Implementing various optimizing techniques to improve performance of the application. 3. How to mutate data in live application.CHAPTER 10. PROJECT BUILDChapter Goal: Finally, we will discuss to build and run complete application on various platforms.No of pages - 10Sub -Topics1. Discuss various application platforms available.2. Pre-requisites to implement developed application on these platforms.3. Implement and run the project.4. Test application on deployment and create requirement files for it.CHAPTER 11. USE CASE: NLP PROJECT PROTOTYPEChapter Goal: This chapter discusses about navigation on the application to be developed. The primary aim is to learn how to switch between multiple pages in an application using navigation.No of pages - 10Sub -Topics1. Pre-requisites.2. NLP module that will be implemented in our application.3. Test application after deployment.CHAPTER 12. USE CASE: COMPUTER VISION PROJECT PROTOTYPEChapter Goal: We will develop a complete streamlit application on Computer Vision from scratch. We will see how all the features we have seen in the above chapters will be implemented in this applicationNo of pages - 10Sub -Topics1. Pre-requisite.2. Computer Vision techniques that needs to implemented.3. Test all functions implemented on our deployed application.
Introducing Spring Framework 6
Spring Framework 6 remains - by far - the leading de-facto "out of the box" practical Java meta application development framework for building complex enterprise, cloud-native applications as well as web applications and microservices. INTRODUCING SPRING FRAMEWORK 6 is your hands-on tutorial guide for learning the Spring Framework 6 from top to bottom, and allows you to build an example application along the way from the ground-up.As you learn the Spring Framework over the course of this book, you’llincrementally build your first Spring application piece-by-piece as you learn each module, project or component of the Spring Framework and its extensions and ecosystem. As you learn the various fundamentals, you'll then apply them immediately to your Spring application. This Spring application, My Documents, enables you to learn by doing.After reading this book, you will have the essentials you should need to start using the Spring Framework and building your own Java-based applications or microservices with it.What you'll learn:* Get started with Spring Framework 6 by VMWare Tanzu and the Spring community* Build your first My Documents application using Spring Framework and its extensions* Test your Spring application* Add persistence to your application using Spring Data JPA and more* Show your Spring application on the Web with Spring MVC and related* Use REST APIs to enhance your application and add messaging with Kafka and AMQP* Integrate your Spring application with external systems using Spring Integration toolkitWho is this book for:This book is for those aspiring software developers and programmers who are new to Spring. Some prior programming experience recommended, preferably in Java. Felipe Gutierrez is a Sr. Cloud Application Architect at IBM, currently. More generally, he is a Software Architect, Application Developer and Project Manager with knowledge on Financial, Educational, Government and Medical Industries. He is interested in Legacy and Enterprise Integration, and large projects. Felipe is dedicated to Enterprise Open Source Software. And, he is experienced on any Java Technology and Java Frameworks, such Spring, Spring Web Services, Spring Integration, Groovy and Grails, Hibernate, iBatis, ActiveMQ, Camel, RabbitMQ, FUSE, ServieMix, .NET Framework (Languages - VB, C#, Boo, C, and C++), Action Script (Flex, Flash) and Silverlight, Mono and Moonlight.JOSEPH B. OTTINGER is an expert software developer, coder and programmer. He has also served as technology evangelist GigaSpaces and a principle engineer at Red Hat. He was Editor in Chief of TheServerSide-dot-com. He is the author of Hibernate Recipes and Beginning Hibernate for Apress and has authored other books as well as articles.1. Your First Spring Application2. Working with Classes and Dependencies3. Applying Different Configurations4. Using Bean Scopes5. Working with Collections and Custom Types6. Using Resource Files7. Testing Your Spring Application8. Give Advice to Your Spring Application9. Adding Persistence to Your Spring Application with Spring Data JPA10. Showing Your Spring Application on the Web with Spring MVC and WebFlow11. Integrating Your Spring Application with External Systems: Spring Integration12. Exposing a REST API using Spring REST13. Adding E-mail and Scheduling Tasks14. Using Dynamic Languages15. Spring Data Within Your Spring Application16. Messaging with Your Spring Application: Spring AMQP and Kafka17. Be Social and Go Mobile18. Spring and Groovy19. Spring Boot, Simplifying Everything20. Using Spring Native and Reactive SpringA. Tools: IntelliJ IDEA and Eclipse Java IDE
C++ Das Übungsbuch (6. Auflage)
Das Buch wendet sich an Leser, die ihre C++-Kenntnisse durch »Learning by Doing« vertiefen möchten. Es ist ideal, um sich im Stil eines Workshops auf Prüfungen oder auf die Mitarbeit in einem C++-Projekt vorzubereiten.Alle Kapitel beginnen mit einer Zusammenfassung des Stoffes, zu dem anschließend Fragen und Aufgaben gestellt werden. Jedes Kapitel besteht neben der einführenden Beschreibung des Themas aus drei weiteren Teilen: Verständnisfragen, Programmieraufgaben und Musterlösungen zu allen Fragen und Aufgaben.Mit jeweils 20 Verständnisfragen können Sie testen, wie gut Sie sich in dem jeweiligen Themenbereich auskennen. Sie finden Ja-Nein- und Multiple-Choice-Fragen sowie Lückentexte, die vervollständigt werden müssen.Im Aufgabenteil können Sie dann Ihr Wissen praktisch umsetzen. In jedem Kapitel gibt es mindestens zehn Aufgaben mit steigendem Schwierigkeitsgrad. Dabei wurde stets darauf geachtet, dass diese typisch und praxisnah sind.Umfangreich kommentierte Musterlösungen am Ende eines Kapitels geben Ihnen ein direktes und ausführliches Feedback zu Ihren Lösungsansätzen.Der Aufbau dieses Übungsbuches lehnt sich an das Lehrbuch »C++ – Lernen und professionell anwenden« derselben Autoren an, das den neuesten ISO-Standard von 2020 (kurz C++20) berücksichtigt und ebenfalls im mitp-Verlag erschienen ist. Es ist aber für das Übungsbuch nicht wesentlich, auf welcher Grundlage Sie C++ gelernt haben.Nach dem Durcharbeiten des Übungsbuches verfügen Sie über fundierte Programmierkenntnisse und einen umfangreichen Fundus an Beispiel-Code.Aus dem Inhalt:Datentypen und KontrollstrukturenVerwendung von StandardklassenOperatoren, Makros, FunktionenVektoren und StringsZeiger und ReferenzenSpeicherreservierung zur LaufzeitKlassen, TeilobjekteDynamische ElementeVererbungPolymorphe Klassen, abstrakte KlassenÜberladen von Funktionen und OperatorenNamensbereicheAusnahmebehandlungDateiverarbeitung mit StreamsAutoren:Prof. Dr. Ulla Kirch unterrichtet an der FH München und Dr. Peter Prinz ist Software-Entwickler. Die Autoren haben bereits zahlreiche Bücher zu C und C++ geschrieben.Leseprobe (PDF-Link)
Building Enterprise IoT Solutions with Eclipse IoT Technologies
Build IoT solutions for the enterprise using open-source building blocks from the Eclipse IoT Working Group at the Eclipse Foundation. This book introduces you to key protocols and their implementations, such as CoAP (Eclipse Californium), DDS (Eclipse Cyclone DDS), LwM2M (Eclipse Leshan), and MQTT (Eclipse Paho, Eclipse Mosquitto, and Eclipse Amlen). You will learn about Edge Computing platforms (Eclipse ioFog, Eclipse Kanto), IoT gateways (Eclipse Kura, Eclipse Kapua), and next-generation edge native protocols (Eclipse zenoh).The book also covers production-ready platforms for digital twins (Eclipse Ditto), energy management (Eclipse VOLTTRON), contactless payments (Eclipse Keyple), and much more.Although the book discusses hardware matters, its focus is on software and relevant open standards. The book helps you understand the pros and cons of the technologies available from Eclipse IoT and how they have been used in actual deployments. The examples provided cover a variety of use cases, such as industrial automation, smart agriculture, digital buildings, robotics, and others.The book's contents follow a reference architecture encompassing constrained devices (things), edge devices (gateways, servers), and IoT Cloud platforms. For each of those three pillars, you will learn about relevant open-source components. Usage of code libraries and frameworks is explained through code samples. You will also learn how to deploy and configure platform-type components and how to leverage them. Special attention will be paid to security and edge computing throughout the book.WHAT YOU WILL LEARN* Describe in your own words the main software components required in an IoT architecture* Select the appropriate IoT protocols, components, frameworks, and platforms for a specific project* Evaluate the connectivity options at your disposal and select the most appropriate ones* Explain the value of business models focused on open-source components and deploy such models in your organization* Determine if edge computing is relevant to a project and deploy the relevant components on an edge computing platform* Build Enterprise IoT solutions leveraging an array of open-source components and platforms using popular languages such as C, Java, and RustWHO THIS BOOK IS FORDevelopers new to enterprise IoT who want to learn about fundamental technologies for that market segment and seek an introduction to relevant, open-source building blocks; experienced IoT developers who seek alternatives to the proprietary platforms they are currently using; software architects designing IoT solutions who want to understand open-source technology optionsFRÉDÉRIC DESBIENS manages IoT and Edge Computing programs at the Eclipse Foundation. His job is to help the community innovate by bringing together devices and software. He is a strong supporter of open source. In the past, he worked as a product manager, solutions architect, and developer for companies as diverse as Pivotal, Cisco, and Oracle. He has an MBA in electronic commerce, a BASc in Computer Science and a BEd, all from Université Laval. After work hours, Frédéric likes to read a history book, play video games, or watch anime.PART I. FUNDAMENTALS AND PROTOCOLS.- 1. What is IoT?.- 2. CoAP.- 3. LwM2M.- 4. MQTT.- 5. Sparkplug.- 6. DDS.- 7. zenoh.- PART II. CONSTRAINED DEVICES.- 8. The Hardware.- 9. Connectivity.- 10. Operating Systems.- PART III. EDGE COMPUTING AND IOT PLATFORMS.- 11. Edge Computing.- 12. Applications.- 13. Integration and Data.- 14. Conclusion.
Building Modern Business Applications
Discover a new way of thinking about business applications in light of the massive industry shift toward cloud computing and reactive programming technologies. This book synthesizes technologies and techniques such as event sourcing, command query responsibility segregation (CQRS), property-based testing, and GraphQL into a cohesive guide for modern business applications that benefit every developer.The book begins with a look at the fundamentals of modern business applications. These fundamentals include business rules and the managing of data over time. The benefits of reactive techniques are explained, including how they are fundamentally aligned with what application developers strive to achieve in their work.Author Peter Royal equips you with sound guidance to follow as you evolve your existing systems, as well as examples of how to build those systems using modern techniques in Spring, Java, and PostgreSQL.WHAT YOU WILL LEARN* Architect business applications for cloud-based environments* Design sustainable business applications* Integrate GraphQL best practices into business applications* Use property-based testing to exhaustively test possible system states* Think about business applications in terms of message flows* Relate the benefits of reactive systems to business goals* Model time appropriately for business requirementsWHO THIS BOOK IS FORPracticing software developers who are building business applications, developers who are being asked to deploy into cloud environments that are more volatile than statically provisioned data centers, developers who want to increase the reliability of their systems and are struggling to find the right paradigms and architectures to achieve their goals, developers who see and use capabilities in software in other areas of their lives and want to bring those capabilities into their own work, and developers with experience designing other types of software who want to learn how to design business applicationsPETER ROYAL is a software developer currently residing in Los Angeles, CA. He has been writing software since high school, with his first business application being a calendar tool for his school. Since then, he has written business applications for a variety of industries as a contractor or in-house developer. He enjoys building tools for co-workers and being able to work with colleagues to iterate and customize, with the goal of making tools that are not frustrating to use. He has come to appreciate pragmatic architectures and practices that enable systems to thrive for the long-term. PART I. ON BUSINESS APPLICATIONS1. What Is A Business Application?2. The Status Quo (and How It Can To Be)PART II. DESIGN PREREQUISITES3. What Is A Reactive System?4. Why Build Business Applications as Reactive Systems?5. What Is A Business Rule?6. Managing TimePART III. DESIGN7. Constraints and Principles8. High-Level Data Flow9. Command Processor10. Command Generator11. Event Materializer12. Testing, Monitoring, and Observability13. Required TechnologiesPART IV. IMPLEMENTATION14. Building with Modern Spring, Java, and PostgreSQL15. Expansion Points and Beyond
C++ Das Übungsbuch
* TRAINIEREN SIE IHRE C++-KENNTNISSE* MIT KOMMENTIERTEN MUSTERLÖSUNGEN* FÜR STUDIUM UND SELBSTSTUDIUMDas Buch wendet sich an Leser, die ihre C++-Kenntnisse durch »Learning by Doing« vertiefen möchten. Es ist ideal, um sich im Stil eines Workshops auf Prüfungen oder auf die Mitarbeit in einem C++-Projekt vorzubereiten.Alle Kapitel beginnen mit einer Zusammenfassung des Stoffes, zu dem anschließend Fragen und Aufgaben gestellt werden. Jedes Kapitel besteht neben der einführenden Beschreibung des Themas aus drei weiteren Teilen: Verständnisfragen, Programmieraufgaben und Musterlösungen zu allen Fragen und Aufgaben.Mit jeweils 20 Verständnisfragen können Sie testen, wie gut Sie sich in dem jeweiligen Themenbereich auskennen. Sie finden Ja-Nein- und Multiple-Choice-Fragen sowie Lückentexte, die vervollständigt werden müssen.Im Aufgabenteil können Sie dann Ihr Wissen praktisch umsetzen. In jedem Kapitel gibt es mindestens zehn Aufgaben mit steigendem Schwierigkeitsgrad. Dabei wurde stets darauf geachtet, dass diese typisch und praxisnah sind.Umfangreich kommentierte Musterlösungen am Ende eines Kapitels geben Ihnen ein direktes und ausführliches Feedback zu Ihren Lösungsansätzen.Der Aufbau dieses Übungsbuches lehnt sich an das Lehrbuch »C++ - Lernen und professionell anwenden« derselben Autoren an, das den neuesten ISO-Standard von 2020 (kurz C++20) berücksichtigt und ebenfalls im mitp-Verlag erschienen ist. Es ist aber für das Übungsbuch nicht wesentlich, auf welcher Grundlage Sie C++ gelernt haben.Nach dem Durcharbeiten des Übungsbuches verfügen Sie über fundierte Programmierkenntnisse und einen umfangreichen Fundus an Beispiel-Code.AUS DEM INHALT:* Datentypen und Kontrollstrukturen* Verwendung von Standardklassen* Operatoren, Makros, Funktionen* Vektoren und Strings* Zeiger und Referenzen* Speicherreservierung zur Laufzeit* Klassen, Teilobjekte* Dynamische Elemente* Vererbung* Polymorphe Klassen, abstrakte Klassen* Überladen von Funktionen und Operatoren* Namensbereiche* Ausnahmebehandlung* Dateiverarbeitung mit StreamsProf. Dr. Ulla Kirch unterrichtet an der FH München und Dr. Peter Prinz ist Software-Entwickler. Die Autoren haben bereits zahlreiche Bücher zu C und C++ geschrieben.