Allgemein
Full-Stack Web Development with Jakarta EE and Vue.js
Harness the power of Jakarta EE to build sturdy back ends while applying Vue.js on the front end. The demand for modern, high-performing enterprise web applications is growing swiftly. The basic HTML front end is no longer enough to meet customer demands. This book shows you how to unlock professional full-stack web development using Jakarta EE and Vue.js.First, you will review the fundamental concepts of Vue.js and essential features of Jakarta EE. You'll then see how to build web applications through every stage of the process, taking into consideration requirement analysis, data model design, code design, the UI, and technical designs, all the way through to implementation, testing, production deployment, and monitoring. Towards the end of the book, you will also learn about the key design patterns and best practices that underpin professional full-stack web development.Full-stack development is the way forward on the web, and using JakartaEE and Vue.js is a great place to start. Get up-to-speed using this book today.WHAT YOU'LL LEARN* Connect an application's frontend and backend with Vue.js and Jakarta EE* Build enterprise web applications from start to finish* Test, secure and deploy your enterprise web applications* Apply common patterns when building full stack applications* Understand the current IT architecture situation of a company, and define a roadmap to accomplish the company goals* Create decoupled applications using software craftsmanship ideasWHO THIS BOOK IS FORJava/Jakarta EE developers who would like to gain a stronghold on both frontend and backend development. Basic knowledge of Java EE is assumed.Daniel Andres Pelaez Lopez is a software craftsman with 12 years of experience working in the software industry across a variety of domains including the finance, aerospace, entertainment, and government sectors. He is passionate about IT architectures and software development at all levels. He worked as a contractor for Fortune 500 companies like Southwest Airlines and Disney, solving hard problems using the Java ecosystem and participating in the overall solution architecture. He is currently working on Hourly, a fast growing start-up, creating the next generation of payroll systems. He holds a Bachelor's Degree in Computer Science from the University of Quindio, Colombia, and a Master’s Degree in IT Architectures from the University of Los Andes, Colombia. He has participated in all stages of development from software architecture to implementation, from front-end to back-end, using Vue.js, React.js, Java, JavaEE, Spring, AWS infrastructure, and more. He blogs at Coders Tower: https://coderstower.com/ and can be found on Twitter @danielpelaezlo.1. Full Stack Web Development with JakartaEE2. Vue.js as a Front End Layer3. Getting Started with Vue.js4. Requirement Analysis for your Full Stack Web Application.5. Modeling your Entities and Data with JPA6. Designing your Front End UI with Vue.Js Components7. Creating Your Back End with Jakarta EE8. Connecting your UI with Your Back End9. Securing Your Full Stack Application10. Authentication and Authorization11. Design Patterns and Best Practices12. Cloud Architecture Implementation13. Continuous Integration and Deployment14. Testing and Monitoring
User-Driven Applications for Research and Science
Build programs that give users full control of their applications in order to meet end users' unique needs and scenarios.Over the last couple of decades, there has been an ongoing quandary in the developer world. Developers are enlisted to build applications to meet users’ demands; users get applications that meet the criteria from the developers’ point of view, but they are far from what the users envisioned. The difference is often wide and nearly catastrophic in fields where users’ actions are nearly impossible to predict, such as science, research work, financial analysis, and others. End users get frustrated with the applications because they were not built with their use cases in mind. For a long time, it was assumed that the developers who created the code should drive their programs and be responsible for all scenarios. While generally not an issue in simple programs, this view is wrong for complex applications in the field of science. These end users are the best specialists in their respective fields and need applications to work beyond the scenarios prepared and allowed for by developers.This book teaches you methods to manage your applications in a way that gives control to your target end users. You will learn proven methods using an easy and predictable instrument, the all-powerful algorithm, to create objects that are movable and re-sizable by users.Get ready to learn by example, using an algorithm of total movability and experience, implemented in different situations. You will begin with the simplest code examples and work your way up to real, complicated programs applicable in STEM fields.WHAT YOU WILL LEARN* Pass the control of your programs from developers to end users* Understand that the most valuable result is not the algorithm itself, but the consequence of using it* Build user-driven applications that include total movability of screen elements* See concepts applied in real situations and scenarios* Be exposed to well-known programs and tasks for developing user-driven applications* Access accompanying code written in C# and available on GitHubWho This Book Is ForDevelopers who want to write or design programs that give their target end users full control over their applicationSERGEY ANDREYEV worked in the Computer Center of the Russian Academy of Sciences. He started on systems for applied optimization, and then he found that he was fascinated by sonogram images. He received a PhD for the design of new algorithms and programming systems for speech analysis. He likes to implement new ideas in new areas and he has designed complicated systems for telecommunications, thermodynamics, and analysis of big electricity networks. He has also worked on applications for foreign language studies and for organizing photo archives. Photography is one of his hobbies.Chapter 1: FoundationChapter 2: Simple ObjectsChapter 3: Complex ObjectsChapter 4: GroupsChapter 5: Graphical analogues of ordinary controlsChapter 6: Elements of data visualizationChapter 7: ExamplesChapter 8: Appendix A: Ordinary controlsChapter 9: Appendix B: Resources
PHP 8 Quick Scripting Reference
This pocket reference has been updated with the new PHP 8 release. It is a condensed, code-rich scripting and syntax handbook for the PHP scripting language. You won’t find any technical jargon, bloated samples, drawn-out history lessons or witty stories in this book. What you will find is a web scripting language reference that is concise, to the point, and highly accessible. The book is packed with useful information and is a must-have for any PHP programmer or web developer. In it, you will find a concise reference to the PHP 8 scripting language syntax. It includes short, simple, and focused code examples; a well-laid-out table of contents; and a comprehensive index allowing easy review.PHP 8 Quick Scripting Reference presents the essentials of PHP in a well-organized format, including new features in PHP 8 such as the just in time (JIT) compiler, union types, nullsafe operator, null coalescing assignment operator, match expressions, named arguments, throw expressions, static return type, non-capturing catches, reclassified engine warnings and constructor property promotion.WHAT YOU WILL LEARN* Discover what is new in PHP 8 and how to get started with it* Work with variables, operators, strings, arrays, conditionals, loops, and other constructs* Group and reuse code with functions, methods, and namespaces* Use object-oriented features such as classes, inheritance, abstract classes, and interfaces* Import files and retrieve user dataMake use of type declarations and type conversions * Test variables, create references, and use overloading methods* Store user data with cookies and sessions* Deal with errors through error handling, exception handling, and assertionsWHO THIS BOOK IS FORExperienced PHP programmers and web developers who may be new to PHP.Mikael Olsson is a professional web entrepreneur, programmer, and author. He works for an R&D company in Finland where he specializes in software development. In his spare time he writes books and creates websites that summarize various fields of interest. The books he writes are focused on teaching their subject in the most efficient way possible, by explaining only what is relevant and practical without any unnecessary repetition or theory.1. Using PHP2. Variables3. Operators4. Strings5. Arrays6. Conditionals7. Loops8. Functions9. Class10. Inheritance11. Access Levels12. Static13. Constants14. Interface15. Abstracts16. Traits17. Importing Files18. Type Declarations19. Type Conversions20. Variable Testing21. Overloading22. Magic Methods23. User Input24. Cookies25. Sessions26. Namespaces27. References28. Advanced Variables29. Error Handling30. Exception Handling31. Assertions
Modern PyQt
Dive into GUI application development and create useful applications for practical and relevant topics in the fields of business, computer science, and research. This book uses a realistic approach to help get you started designing and building the applications you need while learning new tools along the way.PyQt has a vast collection of tools that you can use to create GUIs, many of which seem to go unexplored. In Modern PyQt, you will go beyond some of the fundamental topics of GUI development in order to begin building useful desktop applications. Through extensive examples and hands-on projects, you will explore how to make applications for data analysis and visualization using graphs, computer vision with OpenCV and PyQt, the basics of networking, handling databases with SQL, and more!Whether you are looking for new ideas to practice your skills as a programmer or you have a specific goal in mind and need some help to get your ideas off the ground, there is something in Modern PyQt for you!WHAT YOU WILL LEARN* Create cross-platform GUIs with Python and PyQt.* Understand the important PyQt classes, widgets, and concepts needed for building interactive and practical applications. * Find out how to embed useful Python modules into your applications to create more advanced GUIs. * Build useful applications that you can improve or make into something completely new with Python and PyQt.WHO THIS BOOK IS FORIntermediate level programmers or above in Python. GUI developers with some experience designing GUIs. Even if they have never used PyQt before, the concepts learned from other toolkits, such as Tkinter or wxPython, can be carried over for developing applications with using PyQt.Joshua Willman began using Python in 2015 when he needed to build neural networks using machine learning libraries for image classification. While building large image data sets for his research, he needed to build a GUI that would simplify the workload and labeling process, which introduced him to PyQt. Since then, he has tried to dive into everything that is Python. He currently works as a Python developer, building projects to help others learn more about coding in Python for game development, AI and machine learning, and programming using micro-controllers. More recently, he set up the site redhuli.io to explore his and others’ interests in utilizing programming for creativity.He is also the author of Beginning PyQt: A Hands-on Approach to GUI Programming.
Swarm Intelligence Optimization
Resource optimization has always been a thrust area of research, and as the Internet of Things (IoT) is the most talked about topic of the current era of technology, it has become the need of the hour. Therefore, the idea behind this book was to simplify the journey of those who aspire to understand resource optimization in the IoT. To this end, included in this book are various real-time/offline applications and algorithms/case studies in the fields of engineering, computer science, information security, and cloud computing, along with the modern tools and various technologies used in systems, leaving the reader with a high level of understanding of various techniques and algorithms used in resource optimization.ABHISHEK KUMAR gained his PhD in computer science from the University of Madras, India in 2019. He is assistant professor at Chitkara University and has more than 80 publications in peer-reviewed international and national journals, books & conferences His research interests include artificial intelligence, image processing, computer vision, data mining and machine learning. PRAMOD SINGH RATHORE has a MTech in Computer Science & Engineering from the Government Engineering College Ajmer, Rajasthan Technical University, Kota India, where he is now an assistant professor. He has more than 60 papers, chapters, and a book to his credit and his research interests are in networking cloud and IoT. VICENTE GARCÍA DÍAZ obtained his PhD in Computer Science in 2011 at the University of Oviedo, Spain where he is now an associate professor in the School of Computer Science. He has published more than 100 publications and his research interests include domain-specific languages, e-learning, decision support systems. RASHMI AGRAWAL obtained her PhD in Computer Applications in 2016 from Manav Rachna International University Faridabad, India, where she is now a professor in the Department of Computer Applications. Her research area includes data mining and artificial intelligence and she has published more than 65 publications to her credit. Preface xv1 A FUNDAMENTAL OVERVIEW OF DIFFERENT ALGORITHMS AND PERFORMANCE OPTIMIZATION FOR SWARM INTELLIGENCE 1Manju Payal, Abhishek Kumar and Vicente García Díaz1.1 Introduction 11.2 Methodology of SI Framework 31.3 Composing With SI 71.4 Algorithms of the SI 71.5 Conclusion 18References 182 INTRODUCTION TO IOT WITH SWARM INTELLIGENCE 21Anant Mishra and Jafar Tahir2.1 Introduction 212.1.1 Literature Overview 222.2 Programming 222.2.1 Basic Programming 222.2.2 Prototyping 222.3 Data Generation 232.3.1 From Where the Data Comes? 232.3.2 Challenges of Excess Data 242.3.3 Where We Store Generated Data? 242.3.4 Cloud Computing and Fog Computing 252.4 Automation 262.4.1 What is Automation? 262.4.2 How Automation is Being Used? 262.5 Security of the Generated Data 302.5.1 Why We Need Security in Our Data? 302.5.2 What Types of Data is Being Generated? 312.5.3 Protecting Different Sector Working on the Principle of IoT 322.6 Swarm Intelligence 332.6.1 What is Swarm Intelligence? 332.6.2 Classification of Swarm Intelligence 332.6.3 Properties of a Swarm Intelligence System 342.7 Scope in Educational and Professional Sector 362.8 Conclusion 37References 383 PERSPECTIVES AND FOUNDATIONS OF SWARM INTELLIGENCE AND ITS APPLICATION 41Rashmi Agrawal3.1 Introduction 413.2 Behavioral Phenomena of Living Beings and Inspired Algorithms 423.2.1 Bee Foraging 423.2.2 ABC Algorithm 433.2.3 Mating and Marriage 433.2.4 MBO Algorithm 443.2.5 Coakroach Behavior 443.3 Roach Infestation Optimization 453.3.1 Lampyridae Bioluminescence 453.3.2 GSO Algorithm 463.4 Conclusion 46References 474 IMPLICATION OF IOT COMPONENTS AND ENERGY MANAGEMENT MONITORING 49Shweta Sharma, Praveen Kumar Kotturu and Prafful Chandra Narooka4.1 Introduction 494.2 IoT Components 534.3 IoT Energy Management 564.4 Implication of Energy Measurement for Monitoring 574.5 Execution of Industrial Energy Monitoring 584.6 Information Collection 594.7 Vitality Profiles Analysis 594.8 IoT-Based Smart Energy Management System 614.9 Smart Energy Management System 614.10 IoT-Based System for Intelligent Energy Management in Buildings 624.11 Smart Home for Energy Management Using IoT 62References 645 DISTINCT ALGORITHMS FOR SWARM INTELLIGENCE IN IOT 67Trapty Agarwal, Gurjot Singh, Subham Pradhan and Vikash Verma5.1 Introduction 675.2 Swarm Bird–Based Algorithms for IoT 685.2.1 Particle Swarm Optimization (PSO) 685.2.1.1 Statistical Analysis 685.2.1.2 Algorithm 685.2.1.3 Applications 695.2.2 Cuckoo Search Algorithm 695.2.2.1 Statistical Analysis 695.2.2.2 Algorithm 705.2.2.3 Applications 705.2.3 Bat Algorithm 715.2.3.1 Statistical Analysis 715.2.3.2 Algorithm 715.2.3.3 Applications 725.3 Swarm Insect–Based Algorithm for IoT 725.3.1 Ant Colony Optimization 725.3.1.1 Flowchart 735.3.1.2 Applications 735.3.2 Artificial Bee Colony 745.3.2.1 Flowchart 755.3.2.2 Applications 755.3.3 Honey-Bee Mating Optimization 755.3.3.1 Flowchart 765.3.3.2 Application 775.3.4 Firefly Algorithm 775.3.4.1 Flowchart 785.3.4.2 Application 785.3.5 Glowworm Swarm Optimization 785.3.5.1 Statistical Analysis 795.3.5.2 Flowchart 795.3.5.3 Application 80References 806 SWARM INTELLIGENCE FOR DATA MANAGEMENT AND MINING TECHNOLOGIES TO MANAGE AND ANALYZE DATA IN IOT 83Kashinath Chandelkar6.1 Introduction 836.2 Content Management System 846.3 Data Management and Mining 856.3.1 Data Life Cycle 866.3.2 Knowledge Discovery in Database 876.3.3 Data Mining vs. Data Warehousing 886.3.4 Data Mining Techniques 886.3.5 Data Mining Technologies 926.3.6 Issues in Data Mining 936.4 Introduction to Internet of Things 946.5 Swarm Intelligence Techniques 946.5.1 Ant Colony Optimization 956.5.2 Particle Swarm Optimization 956.5.3 Differential Evolution 966.5.4 Standard Firefly Algorithm 966.5.5 Artificial Bee Colony 976.6 Chapter Summary 98References 987 HEALTHCARE DATA ANALYTICS USING SWARM INTELLIGENCE 101Palvadi Srinivas Kumar, Pooja Dixit and N. Gayathri7.1 Introduction 1017.1.1 Definition 1037.2 Intelligent Agent 1037.3 Background and Usage of AI Over Healthcare Domain 1047.4 Application of AI Techniques in Healthcare 1057.5 Benefits of Artificial Intelligence 1067.6 Swarm Intelligence Model 1077.7 Swarm Intelligence Capabilities 1087.8 How the Swarm AI Technology Works 1097.9 Swarm Algorithm 1107.10 Ant Colony Optimization Algorithm 1107.11 Particle Swarm Optimization 1127.12 Concepts for Swarm Intelligence Algorithms 1137.13 How Swarm AI is Useful in Healthcare 1147.14 Benefits of Swarm AI 1157.15 Impact of Swarm-Based Medicine 1167.16 SI Limitations 1177.17 Future of Swarm AI 1187.18 Issues and Challenges 1197.19 Conclusion 120References 1208 SWARM INTELLIGENCE FOR GROUP OBJECTS IN WIRELESS SENSOR NETWORKS 123Kapil Chauhan and Pramod Singh Rathore8.1 Introduction 1238.2 Algorithm 1278.3 Mechanism and Rationale of the Work 1308.3.1 Related Work 1318.4 Network Energy Model 1328.4.1 Network Model 1328.5 PSO Grouping Issue 1328.6 Proposed Method 1338.6.1 Grouping Phase 1338.6.2 Proposed Validation Record 1338.6.3 Data Transmission Stage 1338.7 Bunch Hub Refreshing Calculation Dependent on an Improved PSO 1338.8 Other SI Models 1348.9 An Automatic Clustering Algorithm Based on PSO 1358.10 Steering Rule Based on Informed Algorithm 1368.11 Routing Protocols Based on Meta-Heuristic Algorithm 1378.12 Routing Protocols for Avoiding Energy Holes 1388.13 System Model 1388.13.1 Network Model 1388.13.2 Power Model 139References 1399 SWAM INTELLIGENCE–BASED RESOURCES OPTIMIZATION AND ANALYSES AND MANAGING DATA IN IOT WITH DATA MINING TECHNOLOGIES 143Pooja Dixit, Palvadi Srinivas Kumar and N. Gayathri9.1 Introduction 1439.1.1 Swarm Intelligence 1439.1.1.1 Swarm Biological Collective Behavior 1459.1.1.2 Swarm With Artificial Intelligence Model 1479.1.1.3 Birds in Nature 1509.1.1.4 Swarm with IoT 1539.2 IoT With Data Mining 1539.2.1 Data from IoT 1549.2.1.1 Data Mining for IoT 1549.2.2 Data Mining With KDD 1579.2.3 PSO With Data Mining 1599.3 ACO and Data Mining 1619.4 Challenges for ACO-Based Data Mining 162References 16210 DATA MANAGEMENT AND MINING TECHNOLOGIES TO MANAGE AND ANALYZE DATA IN IOT 165Shweta Sharma, Satya Murthy Sasubilli and Kunal Bhargava10.1 Introduction 16510.2 Data Management 16610.3 Data Lifecycle of IoT 16710.4 Procedures to Implement IoT Data Management 17110.5 Industrial Data Lifecycle 17310.6 Industrial Data Management Framework of IoT 17410.6.1 Physical Layer 17410.6.2 Correspondence Layer 17510.6.3 Middleware Layer 17510.7 Data Mining 17510.7.1 Functionalities of Data Mining 17910.7.2 Classification 18010.8 Clustering 18210.9 Affiliation Analysis 18210.10 Time Series Analysis 183References 18511 SWARM INTELLIGENCE FOR DATA MANAGEMENT AND MINING TECHNOLOGIES TO MANAGE AND ANALYZE DATA IN IOT 189Kapil Chauhan and Vishal Dutt11.1 Introduction 19011.2 Information Mining Functionalities 19211.2.1 Classification 19211.2.2 Clustering 19211.3 Data Mining Using Ant Colony Optimization 19311.3.1 Enormous Information Investigation 19411.3.2 Data Grouping 19511.4 Computing With Ant-Based 19611.4.1 Biological Background 19611.5 Related Work 19711.6 Contributions 19811.7 SI in Enormous Information Examination 19811.7.1 Handling Enormous Measure of Information 19911.7.2 Handling Multidimensional Information 19911.8 Requirements and Characteristics of IoT Data 20011.8.1 IoT Quick and Gushing Information 20011.8.2 IoT Big Information 20011.9 Conclusion 201References 20212 SWARM INTELLIGENCE–BASED ENERGY-EFFICIENT CLUSTERING ALGORITHMS FOR WSN: OVERVIEW OF ALGORITHMS, ANALYSIS, AND APPLICATIONS 207Devika G., Ramesh D. and Asha Gowda Karegowda12.1 Introduction 20812.1.1 Scope of Work 20912.1.2 Related Works 20912.1.3 Challenges in WSNs 21012.1.4 Major Highlights of the Chapter 21312.2 SI-Based Clustering Techniques 21312.2.1 Growth of SI Algorithms and Characteristics 21412.2.2 Typical SI-Based Clustering Algorithms 21912.2.3 Comparison of SI Algorithms and Applications 21912.3 WSN SI Clustering Applications 21912.3.1 WSN Services 23312.3.2 Clustering Objectives for WSN Applications 23312.3.3 SI Algorithms for WSN: Overview 23412.3.4 The Commonly Applied SI-Based WSN Clusterings 23512.3.4.1 ACO-Based WSN Clustering 23512.3.4.2 PSO-Based WSN Clustering 23712.3.4.3 ABC-Based WSN Clustering 24012.3.4.4 CS Cuckoo–Based WSN Clustering 24112.3.4.5 Other SI Technique-Based WSN Clustering 24212.4 Challenges and Future Direction 24612.5 Conclusions 247References 25313 SWARM INTELLIGENCE FOR CLUSTERING IN WIRELESS SENSOR NETWORKS 263Preeti Sethi13.1 Introduction 26313.2 Clustering in Wireless Sensor Networks 26413.3 Use of Swarm Intelligence for Clustering in WSN 26613.3.1 Mobile Agents: Properties and Behavior 26613.3.2 Benefits of Using Mobile Agents 26713.3.3 Swarm Intelligence–Based Clustering Approach 26813.4 Conclusion 272References 27214 SWARM INTELLIGENCE FOR CLUSTERING IN WI-FI NETWORKS 275Astha Parihar and Ramkishore Kuchana14.1 Introduction 27514.1.1 Wi-Fi Networks 27514.1.2 Wi-Fi Networks Clustering 27714.2 Power Conscious Fuzzy Clustering Algorithm (PCFCA) 27814.2.1 Adequate Cluster Head Selection in PCFCA 27814.2.2 Creation of Clusters 27914.2.3 Execution Assessment of PCFCA 28214.3 Vitality Collecting in Remote Sensor Systems 28214.3.1 Power Utilization 28314.3.2 Production of Energy 28314.3.3 Power Cost 28414.3.4 Performance Representation of EEHC 28414.4 Adequate Power Circular Clustering Algorithm (APRC) 28414.4.1 Case-Based Clustering in Wi-Fi Networks 28414.4.2 Circular Clustering Outlook 28414.4.3 Performance Representation of APRC 28514.5 Modifying Scattered Clustering Algorithm (MSCA) 28614.5.1 Equivalence Estimation in Data Sensing 28614.5.2 Steps in Modifying Scattered Clustering Algorithm (MSCA) 28614.5.3 Performance Evaluation of MSCA 28714.6 Conclusion 288References 28815 SUPPORT VECTOR IN HEALTHCARE USING SVM/PSO IN VARIOUS DOMAINS: A REVIEW 291Vishal Dutt, Pramod Singh Rathore and Kapil Chauhan15.1 Introduction 29115.2 The Fundamental PSO 29215.2.1 Algorithm for PSO 29315.3 The Support Vector 29315.3.1 SVM in Regression 29915.3.2 SVM in Clustering 30015.3.3 Partition Clustering 30115.3.4 Hierarchical Clustering 30115.3.5 Density-Based Clustering 30215.3.6 PSO in Clustering 30315.4 Conclusion 304References 30416 IOT-BASED HEALTHCARE SYSTEM TO MONITOR THE SENSOR’S DATA OF MWBAN 309Rani Kumari and ParmaNand16.1 Introduction 31016.1.1 Combination of AI and IoT in Real Activities 31016.2 Related Work 31116.3 Proposed System 31216.3.1 AI and IoT in Medical Field 31216.3.2 IoT Features in Healthcare 31316.3.2.1 Wearable Sensing Devices With Physical Interface for Real World 31316.3.2.2 Input Through Organized Information to the Sensors 31316.3.2.3 Small Sensor Devices for Input and Output 31416.3.2.4 Interaction With Human Associated Devices 31416.3.2.5 To Control Physical Activity and Decision 31416.3.3 Approach for Sensor’s Status of Patient 31516.4 System Model 31516.4.1 Solution Based on Heuristic Iterative Method 31716.5 Challenges of Cyber Security in Healthcare With IoT 32016.6 Conclusion 321References 32117 EFFECTIVENESS OF SWARM INTELLIGENCE FOR HANDLING FAULT-TOLERANT ROUTING PROBLEM IN IOT 325Arpit Kumar Sharma, Kishan Kanhaiya and Jaisika Talwar17.1 Introduction 32517.1.1 Meaning of Swarm and Swarm Intelligence 32617.1.2 Stability 32717.1.3 Technologies of Swarm 32817.2 Applications of Swarm Intelligence 32817.2.1 Flight of Birds Elaborations 32917.2.2 Honey Bees Elaborations 32917.3 Swarm Intelligence in IoT 33017.3.1 Applications 33117.3.2 Human Beings vs. Swarm 33217.3.3 Use of Swarms in Engineering 33217.4 Innovations Based on Swarm Intelligence 33317.4.1 Fault Tolerance in IoT 33417.5 Energy-Based Model 33517.5.1 Basic Approach of Fault Tolerance With Its Network Architecture 33517.5.2 Problem of Fault Tolerance Using Different Algorithms 33717.6 Conclusion 340References 34018 SMART EPILEPSY DETECTION SYSTEM USING HYBRID ANN-PSO NETWORK 343Jagriti Saini and Maitreyee Dutta18.1 Introduction 34318.2 Materials and Methods 34518.2.1 Experimental Data 34518.2.2 Data Pre-Processing 34518.2.3 Feature Extraction 34618.2.4 Relevance of Extracted Features 34618.3 Proposed Epilepsy Detection System 34918.4 Experimental Results of ANN-Based System 35018.5 MSE Reduction Using Optimization Techniques 35118.6 Hybrid ANN-PSO System for Epilepsy Detection 35318.7 Conclusion 355References 356Index 359
Dynamics 365 Field Service
Configure and customize Microsoft Dynamics 365 Field Services to help your organization deliver onsite service to customer locations. This book will guide you in setting up and implementing Dynamics 365 Field Services to automate workflow and schedule algorithms for mobile users.The book starts with an introduction to Field Services and setting up your Dynamics 365 subscription. Next, you will configure your application. You are shown how to allocate work, manage resources, and move inventory. You will configure both Field Services and the new Field Services Mobile app. One of the main topics covered is applying security to both Field Services and the Field Services Mobile App and how to use both flavors of the application to implement effective solutions. You will go through examples to understand and apply the concepts and features for configuration of Field Services. You also will learn best practices for configuring and customizing Field Services.After reading this book, you will be able to develop and implement enterprise-scale solutions using Dynamics 365 Field Services.WHAT WILL YOU LEARN* Create and process Work Orders* Manage inventory movement in the field* Set up security in Field Services and Field Services Mobile App* Generate Work Orders with agreement* Utilize Microsoft Power Automate with Field ServiceWHO IS THIS BOOK FORTechnical and functional consultants who have Dynamics 365 CE development experienceSANJAYA YAPA currently works as a Microsoft Dynamics CE/FS Solution Architect in Melbourne, Australia. He has more than 14 years of experience in the industry. He has been working with various Microsoft technologies since 2005 and possess a wealth of experience in software development, team leadership, product management, and consultancy. He specializes in Dynamics 365 Customer Engagement, Field Services, and Application Life Cycle Management.INDIKA ABAYARATHNE is from Melbourne, Australia and currently works as a Lead Consultant/Solution Architect. He started the Dynamics CRM journey in 2008 and performed different roles in software development and in consultancy. He blogs on development experience, technology, sharing knowledge, and his expertise via crmfortress.com.CHAPTER 1: DYNAMICS 365 FIELD SERVICESCHAPTER GOAL:This is the initial chapter and the objective is to lay the foundation for the rest of the book. It begins with giving a brief introduction to the Field Services and provide a step by step guideline to setup Field Services. Also, provide the guidelines for setting up the Woodford Configuration tool for Field Service Mobile app configuration. At the end of the chapter, there will be an introduction to the example scenario which will be used to explain the features.NO OF PAGES: 20 PagesSUB -TOPICS1. Introduction to Dynamics 365 Field Services2. Installing Dynamics 365 Field Services3. Installing Woodford Configuration4. Installing the mobile app on desktop and on Android Devices5. The example scenario.CHAPTER 2: CORE ENTITIES AND WOODFORD CONFIGURATIONCHAPTER GOAL: The second chapter is dedicated to describing the core entities and basics of Woodford configuration for Field Services Mobile App. The first half of this chapter will explain the core entities of Field Services App and how these entities can best be used for meeting client demands. The second half of this chapter will give quick walkthrough about Woodford Configuration. Finally, on how to apply the security in both Field Services and the Mobile App.NO OF PAGES: 30 PagesSUB - TOPICS1. Core Entities of Dynamics 365 Field Services2. Introduction to Woodford Configuration3. Field Services SecurityCHAPTER 3: WORK ORDERSCHAPTER GOAL: The third chapter will explain how to create a work order and how to schedule and assign the work orders to the resources. The prerequisites for creating the work order is also explained here. This chapter will also explore the setting up of resources in the system. Finally, explain how to configure the mobile app to receive the work orders.NO OF PAGES: 30 PagesSUB - TOPICS:1. Prerequisites for creating a work order2. Create work orders3. Setting up resources4. Scheduling work orders5. Using Crews to schedule work orders6. Configuring mobile app to receive work ordersCHAPTER 4: CREATE WORK ORDERS AUTOMATICALLYCHAPTER GOAL: There are other ways of creating work orders and the fourth chapter will mainly discuss the most common ways: Generate work orders via Agreements, Generate work orders via external inputs using technologies like Azure Logic Apps. This chapter will also clarify how to configure the mobile interface to create work orders from the mobile app and assign to the users.NO OF PAGES: 30 PagesSUB - TOPICS:1. Generate work orders with Agreement2. Generate work orders from external inputs3. Create work orders from the Mobile App.CHAPTER 5: SETTING UP INVENTORYCHAPTER GOAL: Setting up Inventory for the application is one of the key aspects and chapter 5 will explain how to set up the inventory in the system. This chapter will describe how to setup Products, Services, Price Lists, Tax, and Discounts. The other important part of the inventory is set up the Warehouse structure and the Product Inventory for the warehouse.NO OF PAGES: 25 PagesSUB - TOPICS:1. Setting up Products and Services for Field Services2. Setting up Price Lists, Tax and Discounts3. Setting up the Warehouses4. Add Product Inventory to Warehouse with Inventory Adjustment5. Configuring the mobile app and view inventory on the MapCHAPTER 6: INVENTORY MOVEMENTCHAPTER GOAL: Chapter 6 describes how to track the inventory movement in the field which enables the live inventory feed. This chapter will explain Inventory Transfers, Purchase Orders, RMA and RTA concepts.NO OF PAGES: 25 PagesSUB - TOPICS:1. Inventory Transfers2. Purchase Orders3. RMA (Return Merchandise Authorization)4. RTV (Return to Vendor)5. Using Mobile App to for Inventory MovementCHAPTER 7: EXECUTION AND COMPLETING WORK ORDERSCHAPTER GOAL: The final chapter is dedicated to providing a full end to end process of completing a work order. This chapter will explain the processes after completing the work order. This chapter will discuss in detail the steps to complete the work order assigned to the resource. Microsoft Power Automate is gaining more popularity in the community and in this chapter the reader can gain an understanding of how to utilize it with Field Services.NO OF PAGES: 30 PagesSUB - TOPICS:1. Add products and Services2. Accept customer signature3. Capture payments from the mobile app4. Capture Notes and Signature5. Complete the work order6. Generate Invoice and email to the client
Advanced Excel Success
Explore advanced skills in Excel and gain an amazing array of tricks and tools to increase your productivity. This book discusses new techniques such as power functions, chart tricks, and many more to master Excel.Advanced Excel Success starts with a few useful data tools in Excel followed by advanced formulas that will help you increase productivity. Here, you will learn power functions that aggregate, return ranges, and much more. Further, you will look at custom formatting tricks along with advanced charting tricks. These include automatically changing the color of key metrics, dynamically sorting chart data, and building creative labels.Next, you will understand the role of Power Query which is one of the most important upgrades in Excel. Power Query is the Microsoft Data Connectivity and Data Preparation technology that enables business users to seamlessly access data stored in hundreds of data sources and reshape it to fit their needs, with an easy–to-use, engaging, and no-code user experience. Finally, you will learn Power Pivot which is a distinct feature in Excel that goes beyond spreadsheets.After reading this book, you will be well equipped to work on Excel with its advanced features.WHAT YOU WILL LEARN* Work with the most useful data tools * Understand formulas and the ten power functions* Use advanced chart and formatting tricks and techniques for dynamic and effective visuals* Work with power toolsWHO THIS BOOK IS FORExcel users looking to take the next step to expert level.ALAN is a Microsoft MVP, Excel trainer, YouTuber, and freelance writer. He has been helping people in Excel for over 20 years. He loves training and the joy he gets from knowing he is making people's working lives easier.Alan runs his own blog - Computergaga - and writes for multiple other websites. His YouTube channel has over 500 videos and over 24 million views. He organizes a monthly Excel meetup in London where the Excel community learns, shares, and enjoys each other’s company.CHAPTER 1: EXCEL TRICKS AND DATA TOOLSCHAPTER GOAL: A look at the most useful Data tools in Excel.NO OF PAGES: 40This chapter shows tricks and Excel tools to boost productivity. Features such as Text to Columns and Find and Replace that are known by many Excel users. But not a way shown in this chapter. It also covers some lesser known Data tools.CHAPTER 2: THE 10 POWER FUNCTIONS OF EXCELCHAPTER GOAL: Learn advanced Excel formulas like never before understanding them intimately. Then covering the 10 power functions behind dynamic reports and Excel models with ‘real world’ examples.NO OF PAGES: 60The chapter begins looking at ranges and Boolean expressions in detail. Functions are then categorised – some aggregate, some return ranges. We then move into the power functions and get creative with scenarios they can be used.CHAPTER 3: ADVANCED FORMATTING TECHNIQUESCHAPTER GOAL: Learn advanced formatting tricks to add more meaning to your data.NO OF PAGES: 30This chapter will start with some advanced Conditional Formatting techniques. And then take formatting up another step with some very creative uses and unleash the power of Custom Formatting.CHAPTER 4: ADVANCED CHART TRICKSCHAPTER GOAL: Learn advanced chart tricks to make them pop.NO OF PAGES: 40This chapter will cover a variety of advanced charting tricks. These include automatically changing the color of key metrics, dynamically sort chart data and make them time relative and build creative labels.CHAPTER 5: POWER QUERY – YOU WILL NEVER WORK THE SAME WAYCHAPTER GOAL: To understand the role of Power Query and how it will change the way you work with data.NO OF PAGES: 60This chapter is a guide to Power Query, one of the most important upgrades in Excel history. The chapter walks through several examples using Power Query to streamline coming data tasks and preparing data for analysis.CHAPTER 6: POWER PIVOT – THE INTERNAL DATA MODEL OF EXCELCHAPTER GOAL: An introduction guide to Power Pivot.NO OF PAGES: 60This chapter is a guide to Power Pivot, a feature that goes beyond the Excel spreadsheet. With Power Pivot we can store huge volumes of data, model it and perform powerful calculations. This is all covered in the chapter.
Beginning MLOps with MLFlow
Integrate MLOps principles into existing or future projects using MLFlow, operationalize your models, and deploy them in AWS SageMaker, Google Cloud, and Microsoft Azure. This book guides you through the process of data analysis, model construction, and training.The authors begin by introducing you to basic data analysis on a credit card data set and teach you how to analyze the features and their relationships to the target variable. You will learn how to build logistic regression models in scikit-learn and PySpark, and you will go through the process of hyperparameter tuning with a validation data set. You will explore three different deployment setups of machine learning models with varying levels of automation to help you better understand MLOps. MLFlow is covered and you will explore how to integrate MLOps into your existing code, allowing you to easily track metrics, parameters, graphs, and models. You will be guided through the process of deploying and querying your models with AWS SageMaker, Google Cloud, and Microsoft Azure. And you will learn how to integrate your MLOps setups using Databricks.WHAT YOU WILL LEARN* Perform basic data analysis and construct models in scikit-learn and PySpark* Train, test, and validate your models (hyperparameter tuning)* Know what MLOps is and what an ideal MLOps setup looks like* Easily integrate MLFlow into your existing or future projects* Deploy your models and perform predictions with them on the cloudWHO THIS BOOK IS FORData scientists and machine learning engineers who want to learn MLOps and know how to operationalize their modelsSRIDHAR ALLA is the co-founder and CTO of Bluewhale, which helps big and small organizations build AI-driven big data solutions and analytics. He is a published author of books and an avid presenter at numerous Strata, Hadoop World, Spark Summit, and other conferences. He also has several patents filed with the US PTO on large-scale computing and distributed systems. He has extensive hands-on experience in several technologies, including Spark, Flink, Hadoop, AWS, Azure, Tensorflow, Cassandra, and others. He spoke on Anomaly Detection Using Deep Learning at Strata SFO in March of 2019 and at Strata London in October of 2019. He was born in Hyderabad, India and now lives in New Jersey, USA with his wife Rosie and daughter Evelyn. When he is not busy writing code, he loves to spend time with his family and also training, coaching, and organizing meetups.SUMAN KALYAN ADARI is an undergraduate student pursuing a BS degree in computer science at the University of Florida. He has been conducting deep learning research in the field of cybersecurity since his freshman year, and has presented at the IEEE Dependable Systems and Networks workshop on Dependable and Secure Machine Learning held in Portland, Oregon, USA in June of 2019. He is passionate about deep learning, and specializes in its practical uses in various fields such as image recognition, anomaly detection, natural language processing, targeted adversarial attacks, and more.Chapter 1: Getting Started: Data Analysis and Feature EngineeringChapter Goal: Establish the premise of the problem we want to solve with machine learning. Analyze several data sets and process them.No of pages - 30 pagesSub - Topics1. Premise4. Data analysis5. Feature engineeringChapter 2: Building a Machine Learning ModelChapter Goal: Build a machine learning model on a data set / several data sets that we processed the data for in chapter 4.No of pages – 40 pagesSub - Topics:1. Building the model2. Training and testing the model3. Validation and optimizingChapter 3: What is MLOps?Chapter Goal: Introduce the reader to MLOps, various stages of automation in MLOps setups, automation with pipeline, and to CI/CD and CD Deployment.Pipelines for: source repo to deployment, prediction services, performance monitoring, etcContinuous Integration (source repo updated with new models), and Continuous Delivery (new models deployed).No of pages – 40 pagesSub -Topics1. What is MLOps?2. MLOps setups3. Automation4. CI/CD – Continuous Integration & Delivery5. CD - DeploymentChapter 4: Introduction to MlFlowChapter Goal: Introduce the reader to MLFlow and how to incorporate MLFlow into our ML training process (PyTorch, Keras, TensorFlow)No of pages – 30 pagesSub - Topics:1. What is MLFlow?2. MLFlow in PyTorch3. MLFlow in Keras4. MLFlow in TensorFlowChapter 5: Deploying in AWS – 40 pagesChapter Goal: Guide the reader through the process of deploying an MLOps setup on AWS SageMaker.-Description: The chapter will walk the reader through AWS SageMaker and help them deploy their MLOps setup (data processing scripts, model train, test, validation scripts) in AWS.Chapter 6: Deploying in Azure – 40 pagesChapter Goal: Guide the reader through the process of deploying an MLOps setup on Microsoft Azure.-Description: The chapter will walk the reader through Microsoft Azure and help them deploy their MLOps setup (data processing scripts, model train, test, validation scripts) in Azure.Chapter 7: Deploying in Google – 40 pagesChapter Goal: Guide the reader through the process of deploying an MLOps setup on Google Cloud.-Description: The chapter will walk the reader through Google Cloud and help them deploy their MLOps setup (data processing scripts, model train, test, validation scripts) in Google Cloud.Appendix A: a2ml – 20 pagesChapter Goal: This appendix chapter is optional and guides users through the process of deploying an MLOps setup using a2ml.-Description: The chapter will walk the reader through a2ml and help them deploy their MLOps setup (data processing scripts, model train, test, validation scripts) through a2ml.
Pro Google Cloud Automation
Discover the methodologies and best practices for getting started with Google cloud automation services including Google Cloud Deployment Manager, Spinnaker, Tekton, and Jenkins to automate deployment of cloud infrastructure and applications.The book begins with an introduction to Google cloud services and takes you through the various platforms available to do automation on the GCP platform. You will do hands-on exercises and see best practices for using Google Cloud Deployment Manager, Spinnaker, Tekton, and Jenkins. You’ll cover the automation aspects of the Google Cloud Platform holistically using native and upcoming open source technologies.The authors cover the entire spectrum of automation from cloud infrastructure to application deployment and tie everything together in a release pipeline using Jenkins. Pro Google Cloud Automation provides in-depth guidance on automation and deployment of microservices-based applications running on the Kubernetes platform. It provides sample code and best practice guidance for developers and architects for their automation projects on the Google Cloud Platform.This book is a good starting point for developers, architects, and administrators who want to learn about Google cloud automation.WHAT YOU WILL LEARN* Gain the fundamentals of Google’s automation-enabling services* See an architecture overview for Google Cloud Deployment Manager, Spinnaker, Tekton, and Jenkins* Implement automation for infrastructure and application use cases* Automate microservices-based applications running on GKE* Enable Google Cloud Deployment Manager, Spinnaker, Tekton, and Jenkins WHO THIS BOOK IS FORDevelopers, architects, and administrators who want to learn about Google cloud automation.Navin Sabharwal is an innovator, thought leader, author, and consultant in the areas of cloud computing, cloud lifecycle management, infrastructure as code, DevSecOps, AI, machine learning, big data analytics, and AIOPS. Navin has created niche award-winning products and solutions and has filed numerous patents in diverse fields such as IT services, assessment engines, ranking algorithms, capacity planning engines, and knowledge management.Piyush is a solution architect for automation, DevOps, and cloud services with overall ten years of IT experience. Piyush is currently working as a deputy general manager at HCL DRYiCE practice focusing on creating solutions catering to cloud adoption (including cloud landing zone, migration, and operations), automation, orchestration, and cloud lifecycle management.Chapter 1- Introduction to Google Cloud Automation Services• Google Cloud introduction• Introduction to Google Cloud Deployment Manager• Introduction to Spinnaker• Introduction to Kubernetes• Introduction to StackdriverChapter 2- Getting Started with Google Cloud Deployment Manager• Architecture overview of Google Cloud Deployment Manager• Hand on use case of Google Cloud Deployment ManagerChapter 3- Getting Started with Spinnaker• Architecture overview of Spinnaker• Getting started with setting up Spinnaker• Setting up integration• Hand on use case of CI/CD pipeline using SpinnakerChapter 4 – Getting Started with Kubernetes• Architecture overview of Kubernetes• Setting up Kubernetes• Hand on use case of GKE automation using KubernetesChapter 5- Getting Started with Stackdriver• Architecture overview of Stackdriver• Hand on use case of GCP monitoring• Runbook Automation use caseChapter 6- DevSecOps Automation• Scenarios of using Google Cloud Automation service• Hands on integrated use case of using all Automation services
Requirements-Engineering und -Management
- Praktische und innovative Lösungen für die Anforderungsanalyse sichern den Know-how-Transfer in Ihrem Entwicklungsvorhaben.- Erlernen Sie das Ermitteln, Vermitteln, Herleiten und Verwalten von qualitativ hochwertigen Anforderungen.- Meistern Sie Ihre Anforderungen in agilen Frameworks sowie in klassischen Vorgehensweisen.- Tauchen Sie ein in die Welt der Smart Ecosystems.- Lernen Sie das Zusammenspiel von Anforderungen und Architektur im Systems-Engineering kennen.Der Erfolg von Systementwicklungen entscheidet sich bereits in der Anforderungsanalyse! Sie ist das Fundament für viele weitere Tätigkeiten.Dieses Buch liefert Ihnen Hintergründe, Strategien, klare Konzepte und umfangreiche Praxistipps zur pragmatischen Umsetzung Ihrer Anforderungen – von der Erhebung bis hin zur Verwaltung.Als neue Themen werden in der 7. Aufl age Requirements-Engineering im agilen Umfeld, Systems-Engineering und Smart Ecosystems betrachtet. Zusätzlich bietet diese Auflage Einblicke in den Einsatz von Videos im Requirements-Engineering, Crowd-RE und die Besonderheiten im Variantenmanagement.Durch die Buchkapitel begleiten Sie ein durchgehendes Beispiel mit einer eigenen Rahmenhandlung und eine von Kapitel zu Kapitel aufbauende Bauanleitung für einen Requirements-Engineering-Leitfaden.Im Internet finden Sie unter www.sophist.de/re7 zusätzliche Formulare, Checklisten, Hintergrundinformationen und vieles mehr.AUS DEM INHALT //Vorgehensweisen klassisch und agil/Anforderungsermittlung/SOPHIST-REgelwerk/Anforderungsschablonen/Anforderungsanalyse/Geschäftsprozesse/Systems-Engineering/Smart Ecosystems (Industrie 4.0)/Anforderungsdokumentation/klassisch und agil/Nichtfunktionale Anforderungen/Prüftechniken für Anforderungen/Anforderungskonsolidierung/Requirements-Management, Change- & Release-Management/Einführungsstrategien/Produktlinien undProduktfamilien/Videos im Requirements-Engineering/Requirements-Engineering mit der Crowd Chris Rupp & Die Sophisten sind Spezialisten für Requirements-Engineering und -Management. Als Berater und Trainer begleiten sie methodisch und operativ in klassischen und agilen Projekten von der Idee über gute Anforderungen bis hin zum passenden System. Die Erfindungen der SOPHISTen prägen die Welt der Anforderungsanalyse.
Wunder Informatik
'Ich habe aus Mangel an guten Alternativen mit dem Informatikstudium begonnen: Mir fiel nichts Besseres ein. Das war mein großes Glück.'Die Informatik ist das wichtigste Werkzeug des 21. Jahrhunderts. Die ganze Welt spricht in den Sprachen der Informatik. Das gilt für alle Bereiche der modernen Welt und zunehmend auch für unser privates Leben. Man kann die Welt ohne Informatik nicht mehr verstehen und nicht mehr verändern.Doch es gibt auch viele Missverständnisse über die Informatik. Das liegt daran, dass sie eine junge Wissenschaft ist, die sich permanent und schnell verändert: von ihren Anfängen in den 1940er-Jahren als Rechenmaschine für Chemiker und Physiker bis zum Smartphone und der Cloud.Dieses Buch ermöglicht eine intuitive Einführung in die Informatik. Es beschreibt die grundlegenden Konzepte und erläutert Teilbereiche wie Data Science, Big Data oder künstliche Intelligenz. Vor allem aber entmystifiziert es die Welt der Informatik anhand vieler Alltagsbeispiele. Es muss nicht jeder Informatik studieren oder ein Experte sein. Doch es soll jeder von ihren Ideen und Innovationen profitieren.Das Buch richtet sich vorwiegend an Jugendliche: Sie erhalten einen Einblick, was sie in einem Studium oder auf dem Berufsweg erwartet. Sie sollen weder zufällig Informatik studieren noch zufällig Informatik nicht studieren. Doch das Buch ist auch für Erwachsene relevant, die eine allgemeinverständliche Einführung suchen, in die auch viele persönliche Erfahrungen eingeflossen sind.
Wie KI unser Leben verändert
100 Fragen - 100 AntwortenSiri, Alexa oder Hey Google kennen die meisten von uns. Vom autonomen Fahren oder dass Sie Vögel mit Apps erkennen können – davon haben Sie sicher schon gehört. Aber inzwischen wird Künstliche Intelligenz in noch viel mehr Bereichen eingesetzt. Welche das sind, erfahren Sie in diesem Buch.Künstliche Intelligenz ist älter, als Sie vermuten! KI hat Vorteile, birgt aber auch Risiken – und sie ist nicht mehr wegzudenken. Deshalb sollte jeder von uns wissen, was KI für seinen Alltag, den Beruf und unser aller Zukunft bedeuten kann.Peter Seeberg hat aus unterschiedlichen Lebensbereichen die wichtigsten 100 Fragen zu KI gesammelt und beantwortet. Machen Sie sich schlau.Leseprobe (PDF-Link)
Beginning Game AI with Unity
Game developers will use this book to gain a basic knowledge of programming artificial intelligence using Unity and C#. You will not be bored learning the theory underpinning AI. Instead, you will learn by experience and practice, and complete an engaging project in each chapter.AI is the one of the most popular subjects in gaming today, ranging from controlling the behavior of non-player characters to procedural generated levels. This book starts with an introduction to AI and its use in games. Basic moving behaviors and pathfinding are covered, and then you move through more complex concepts of pathfinding and decision making.WHAT YOU WILL LEARN* Understand the fundamentals of AI* Create gameplay-based AI to address navigation and decision-making problems* Put into practice graph theory and behavior models* Address pathfinding problems* Use the A* algorithm, the deus ex machina of pathfinding algorithms* Create a mini stealth gameWHO THIS BOOK IS FORDevelopers and programming enthusiasts with a basic knowledge of Unity and C# who want to understand and master the foundations of artificial intelligence in gamesSEBASTIANO COSSU is a software engineer and game developer. He studied computer science at the University of Rome "La Sapienza". He is currently working as Game UI Developer at Feral Interactive Ltd. in London. He wrote the Apress book, Game Development with GameMaker Studio 2.CHAPTER 1: INTRODUCTIONChapter Goal: An introduction to the book where goals and main topics are introduced to the reader.Sub -Topics1. What is AI?2. AI in games3. Intelligent agents4. Knowledge representationCHAPTER 2: MOVEMENTSChapter Goal: Introducing the reader to steering and basic AI moving behaviors, in particular wandering and following the player.Sub - Topics1. Moving in a 2D world2. Moving in a 3D world3. Steering4. Moving behaviors (wandering vs following)5. A case study: car games6. Project: mini car traffic simulatorCHAPTER 3: PATHFINDINGChapter Goal: Introducing the reader to pathfinding algorithms and problem-solving approaches.Sub - Topics:1. Graphs2. Pathfinding algorithms: Dijkstra3. Pathfinding algorithms: A*4. World representation5. Constraint Satisfaction Problems (CSP)6. Improving on pathfinding7. A case study: Warcraft8. Project: LabyrinthCHAPTER 4: DECISION MAKINGChapter Goal: How does AI takes decisions? In this chapter, the reader will understand how to implement the ability to reason and plan actions using data structures to represent knowledge and search algorithms to find the best sequence of actions.Sub - Topics:1. Decision trees2. Finite-state machines (FSM)3. Behavior trees4. Fuzzy logic5. Goal-oriented behavior7. Rule-based systems9. A case study: Halo10. Project: Wumpus’ Cave ExplorerCHAPTER 5: TACTICS AND STRATEGYChapter Goal: Putting together all the knowledge acquired in the previous chapters to build intelligent agents that can perform well against the player.Sub - Topics:1. Putting things together: intelligent agents in action2. Strategy planning3. Tactical pathfinding4. Coordination and tactics in PVE: ambushing the player5. A case study: 007 Goldeneye6. Project: Chess with guns
Quick Guide for Obtaining Free Remote Desktop Protocol (RDP) Services
Remote Desktop Protocol (RDP) is a proprietary protocol developed by Microsoft which provides a user with a graphical interface to connect to another computer over a network connection. The user employs RDP client software for this purpose, while the other computer must run RDP server software.RDP refers to Remote Desktop protocol which connects your remotely connected computers or system over a RDP connected network. RDP gives a graphical interface to a client to be able to associate with another PC, system or network. RDP servers are built on Windows OS, but can be enabled to other OS as well. The major benefit of a remote desktop connection is being able to connect to your data from anywhere in the world. Your data is in one place that is easy to see and you no longer have to have software installed on your own computer.In Simple term RDP is a short form of Remote Desktop Protocol RDP specifies for home windows servers, it works as an icon to get in touch with an additional computer system, usually, it is utilized for attaching to a server organized in a data center to carry out jobs that typically do not need much user interaction and runs 24/7.Several of the extra usual uses of RDP servers are running bots, SEO devices, bitcoin mining, on-line video clip streaming, running forex trading software and so on.Most RDP servers providers that provide free services during trial period will request debit/credit card information, which is risky for us as they can claim any payment from the card. So that encouraged me to search for RDP services providers that can provide services during free trial period without requesting credit/debit card information. This report will investigate the possible ways to get free RDP server account or RDP server account at lowest cost. The report will consist from the following parts: 1.Some RDP Services Providers with free trials2.Some RDP servers providers that sell RDP with Credit Card, Debit Card, Bitcoin, PayPal or other E-wallets 3.Getting free RDP from freerdpserver.com4.Getting free RDP from Google Cloud5.Getting Google Cloud RDP/VPS for free for one month through Qwiklabs.com 6.Creating RDP through Alibabacloud.com7.Getting free RDP/VPS for seven days from CloudSigma.com8.Getting RDP/VPS through Microsoft Azure9.Getting Microsoft Azure RDP/VPS for free through Sandbox subscription10.How to get university email11.How to get RDP service for free through Microsoft Azure for students12.Getting free RDP from AWS Amazon13.How to get free RDP service with Amazon AWS Educate14.Some free websites that can be used to receive SMS online using numbers from some countries15.Generating virtual debit/credit cards using namso gold CC BIN generator for verification of some online services accountsI am Dr. Hidaia Mahmoud Mohamed Alassouli. I completed my PhD degree in Electrical Engineering from Czech Technical University by February 2003, and my M. Sc. degree in Electrical Engineering from Bahrain University by June 1995. I completed also one study year of most important courses in telecommunication and computer engineering courses in Islamic university in Gaza. So, I covered most important subjects in Electrical Engineering, Computer Engineering and Telecommunications Engineering during my study. My nationality is Palestinian from gaza strip.I obtained a lot of certified courses in MCSE, SPSS, Cisco (CCNA), A+, Linux.I worked as Electrical, Telecommunicating and Computer Engineer in a lot of institutions. I worked also as a computer networking administrator. I had considerable undergraduate teaching experience in several types of courses in many universities. I handled teaching the most important subjects in Electrical and Telecommunication and Computer Engineering. I could publish a lot of papers a top-tier journals and conference proceedings, besides I published a lot of books in Publishing and Distribution houses.I wrote a lot of important Arabic articles on online news websites. I also have my own magazine website that I publish on it all my articles: http:// www.anticorruption.000space.comMy personal website: www.hidaia-alassouli.000space.comEmail: hidaia_alassouli@hotmail.com
Eine kurze Geschichte vom Quantencomputer (2. Auflg.) - TELEPOLIS
Quantencomputer anschaulich erklärtDie Welt der Quanten ist total verrückt. Teilchen befinden sich gleichzeitig hier und dort. Sie verständigen sich über tausend Kilometer wie durch Telepathie. Forscher haben diese Phänomene inzwischen so gut im Griff, dass sie einen riesigen technologischen Schritt wagen: Den Bau des ersten Quantencomputers – eine ganz neue, überlegene Art von Rechner.Das Buch erklärt verständlich und unterhaltsam die magisch anmutenden Phänomene der Quantenphysik und wie sie für unbegreiflich schnell rechnende Computer genutzt werden können. Es zeigt, wie der Quantencomputer und andere Technologien, die auf der Quantenphysik basieren, den Alltag ähnlich umwälzen könnten wie einst die Dampfmaschine oder die Entdeckung der Elektronik. Werden Quantencomputer die gängigen Verschlüsselungsverfahren aushebeln? Werden sie eine blitzschnelle Entwicklung neuer Arzneien ermöglichen? Wird es einmal ein Quanteninternet geben und wenn ja, was bringt es? Werden es hyperempfindliche Quantensensoren erlauben, die Gedanken eines Menschen zu lesen? Neben Beispielen schon existierender Quantentechnologie (etwa Flash-Speicher oder Verschlüsselungsverfahren) gibt der Wissenschaftsjournalist Christian J. Meier einen Überblick über die wichtigsten Laborentwicklungen und zeigt auf, wohin sie führen könnten. Schließlich erfahren Sie, warum manche Physiker glauben, das Universum sei ein einziger Quantencomputer.Christian J. Meier (geb. 1968), promovierter Physiker und freier Journalist, beschäftigt sich seit mehreren Jahren mit den Themen Quantencomputer und Quantentechnologie und berichtet darüber für verschiedene Medien, unter anderem für die Neue Zürcher Zeitung, bild der wissenschaft, Berliner Zeitung, Frankfurter Rundschau, Spektrum.de und VDI nachrichten. Inhalt (PDF-Link)Leseprobe (PDF-Link)
Chatbots
Chatbots setzen sich in vielen Bereichen für die Kommunikation mit Kunden, Mitarbeitern und Bürgern durch. Sie beantworten automatisch Anfragen, entlasten Hotlines oder beraten Kunden. In diesem Buch werden die technischen wie auch die sprachlichen Grundlagen von Chatbots ausführlich vorgestellt und anhand von praxisnahen Beispielen erläutert. Weiterhin werden wichtige Aspekte wie Kosten, Akzeptanz und rechtliche Grundlagen beleuchtet. Abschließend wird anhand eines konkreten Beispiels ein Chatbot-Projekt exemplarisch beschrieben.ANDREAS KOHNE ist promovierter Informatiker und leitet den Bereich Business Development eines mittelständigen IT-Unternehmens in Dortmund.PHILIPP KLEINMANNS eitet eine Beratungsabteilung mit Schwerpunkten auf Internet of Things und Customer Service bei einem mittelständischen IT-Anbieter in Dortmund.CHRISTIAN ROLF ist Projektmanager für Digitalprojekte im Bereich Chatbots und Digital Signage bei einer Agentur in Witten.MORITZ BECK ist Gründer und Geschäftsführer einer Unternehmensberatung für Messenger-Kommunikation und Chatbots mit Sitz in Hamburg. Grundlagen.- Bekannte Bots.- Technik.-Anwendungsgebiete.- Design eines Chatbots.- Finanzen.- Recht.- zukünftige Anwendungen.
IT-Prüfung, Datenschutzaudit und Kennzahlen für die Sicherheit
Dieses Buch aus der Reihe „Neue Ansätze für die IT-Revision“ entwickelt aktuelle und neuartige Methoden für die Arbeit der Revision sowie für Prüfungen und Tests von IT-Systemen. Berücksichtigt werden dabei Aspekte des Datenschutzes, der Cybersicherheit, Effektivität und Funktionalität, und es werden Ansätze für Datenschutzbeauftragte, IT-Sicherheitsbeauftragte, CISOs, Compliance-Manager etc. vorgestellt.Die Schwerpunkte des Buches liegen auf Datenschutz, Kennzahlensystemen sowie Internet of Things und Künstlicher Intelligenz. Besondere Beachtung erfahren Themen wie Prüfung des Datenschutzmanagementsystems (DSMS), Prüfung der Auftragsverarbeitung sowie Meldepflichten gemäß DSGVO.Die präsentierten Ansätze zur Bewertung der Informationssicherheit mittels Kennzahlen, zu Tests für IoT-Geräte und zur Zertifizierung der Softwareentwicklung ermöglichen den Revisoren, diese Themen als systematische Prüfungen, Tests und Audits zu erfassen und umzusetzen.DR. ALEKSANDRA SOWA leitete zusammen mit dem deutschen Kryptologen Hans Dobbertin das Horst Görtz Institut für Sicherheit in der Informationstechnik. Sie ist zertifizierte Datenschutzbeauftragte und Datenschutzauditorin, IT-Compliance-Managerin (ITCM) und IT Information Security Practitioner (ITISP). Aleksandra ist Autorin diverser Bücher und Fachpublikationen, trat als Sachverständige für IT-Sicherheit im Innenausschuss des Bundestages auf, war u. a. für den Vorstand Datenschutz, Recht und Compliance (DRC) der Deutschen Telekom AG tätig und ist aktuell Senior Manager und Prokuristin in einer Wirtschaftsprüfungsgesellschaft.Prüfung des Datenschutzmanagementsystems (DSMS) - Prüfung der Auftragsverarbeiter gem. Art. 28 DSGVO - Meldepflichten für „Data Breaches“ gemäß Art. 33 DSGVO - Kennzahlensysteme für Bewertung der Informationssicherheit - Reife der Informationssicherheit - IoT-Penetrationstest - Zertifizierung der Softwareentwicklung
Machine Learning for Time Series Forecasting with Python
LEARN HOW TO APPLY THE PRINCIPLES OF MACHINE LEARNING TO TIME SERIES MODELING WITH THIS INDISPENSABLE RESOURCEMachine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling.Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment of the application of machine learning to time series forecasting.Written for readers who have little to no experience in time series forecasting or machine learning, the book comprehensively covers all the topics necessary to:* Understand time series forecasting concepts, such as stationarity, horizon, trend, and seasonality * Prepare time series data for modeling * Evaluate time series forecasting models’ performance and accuracy * Understand when to use neural networks instead of traditional time series models in time series forecasting Machine Learning for Time Series Forecasting with Python is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts.Perfect for entry-level data scientists, business analysts, developers, and researchers, this book is an invaluable and indispensable guide to the fundamental and advanced concepts of machine learning applied to time series modeling.FRANCESCA LAZZERI is an accomplished economist who works with machine learning, artificial intelligence, and applied econometrics. She works at Microsoft as a data scientist and machine learning scientist to develop a portfolio of machine learning services. She is a sought-after speaker and has given popular talks at AI conferences and academic seminars at Berkeley, Harvard, and MIT.Acknowledgments viiIntroduction xvCHAPTER 1 OVERVIEW OF TIME SERIES FORECASTING 1Flavors of Machine Learning for Time Series Forecasting 3Supervised Learning for Time Series Forecasting 14Python for Time Series Forecasting 21Experimental Setup for Time Series Forecasting 24Conclusion 26CHAPTER 2 HOW TO DESIGN AN END-TO-END TIME SERIES FORECASTING SOLUTION ON THE CLOUD 29Time Series Forecasting Template 31Business Understanding and Performance Metrics 33Data Ingestion 36Data Exploration and Understanding 39Data Pre-processing and Feature Engineering 40Modeling Building and Selection 42An Overview of Demand Forecasting Modeling Techniques 44Model Evaluation 46Model Deployment 48Forecasting Solution Acceptance 53Use Case: Demand Forecasting 54Conclusion 58CHAPTER 3 TIME SERIES DATA PREPARATION 61Python for Time Series Data 62Common Data Preparation Operations for Time Series 65Time stamps vs. Periods 66Converting to Timestamps 69Providing a Format Argument 70Indexing 71Time/Date Components 76Frequency Conversion 78Time Series Exploration and Understanding 79How to Get Started with Time Series Data Analysis 79Data Cleaning of Missing Values in the Time Series 84Time Series Data Normalization and Standardization 86Time Series Feature Engineering 89Date Time Features 90Lag Features and Window Features 92Rolling Window Statistics 95Expanding Window Statistics 97Conclusion 98CHAPTER 4 INTRODUCTION TO AUTOREGRESSIVE AND AUTOMATED METHODS FOR TIME SERIES FORECASTING 101Autoregression 102Moving Average 119Autoregressive Moving Average 120Autoregressive Integrated Moving Average 122Automated Machine Learning 129Conclusion 136CHAPTER 5 INTRODUCTION TO NEURAL NETWORKS FOR TIME SERIES FORECASTING 137Reasons to Add Deep Learning to Your Time Series Toolkit 138Deep Learning Neural Networks Are Capable of Automatically Learning and Extracting Features from Raw and Imperfect Data 140Deep Learning Supports Multiple Inputs and Outputs 142Recurrent Neural Networks Are Good at Extracting Patterns from Input Data 143Recurrent Neural Networks for Time Series Forecasting 144Recurrent Neural Networks 145Long Short-Term Memory 147Gated Recurrent Unit 148How to Prepare Time Series Data for LSTMs and GRUs 150How to Develop GRUs and LSTMs for Time Series Forecasting 154Keras 155TensorFlow 156Univariate Models 156Multivariate Models 160Conclusion 164CHAPTER 6 MODEL DEPLOYMENT FOR TIME SERIES FORECASTING 167Experimental Set Up and Introduction to Azure Machine Learning SDK for Python 168Workspace 169Experiment 169Run 169Model 170Compute Target, RunConfiguration, and ScriptRun Config 171Image and Webservice 172Machine Learning Model Deployment 173How to Select the Right Tools to Succeed with Model Deployment 175Solution Architecture for Time Series Forecasting with Deployment Examples 177Train and Deploy an ARIMA Model 179Configure the Workspace 182Create an Experiment 183Create or Attach a Compute Cluster 184Upload the Data to Azure 184Create an Estimator 188Submit the Job to the Remote Cluster 188Register the Model 189Deployment 189Define Your Entry Script and Dependencies 190Automatic Schema Generation 191Conclusion 196References 197Index 199
Migrating a Two-Tier Application to Azure
Understand and build a proof of concept by migrating a multi-tiered .NET Core web application to the Azure public cloud, leveraging different Azure Infrastructure as a Service (IAAS), Azure Platform as a Service (PaaS), and Azure Container offerings. These include Azure Container Instance (ACI), Azure Kubernetes Services (AKS), and CI/CD pipeline deployments using Azure DevOps.After a first chapter in which you set up the baseline for the lab scenarios, you will start with the basics of automating Azure resource deployments using Visual Studio and powerful Azure Resource Manager (ARM) templates. Next, you’ll learn about the importance of performing proper assessments and the tools Microsoft offers to help in this migration preparation phase. After that, you will validate the virtual machine deployment and learn about SQL Server database migration to SQL Azure PaaS, as well as deploying and migrating web applications to Azure Web Apps.After covering these foundational platform components, the next chapters focus on the core concepts and advantages of using containers for running business workloads. These labs are based on Docker, Azure Container Registry (ACR), ACI, and Web App for Containers, and show you how to enable container orchestration and cloud-scale using AKS.In the last part of the book, you will work with Azure DevOps, the Microsoft application lifecycle environment, building a CI/CD pipeline to publish workloads using the DevOps principles and concepts. You’ll see the integration with the rest of the Azure services, closing with a module on overall Azure monitoring and operations and what tools Azure has available to assist your IT teams in this challenge.WHAT YOU WILL LEARN* Use Azure to enable digital transformation* Carry out Azure automated deployments using ARM templates and Azure DevOps* Run VM-based workloads on Azure* Migrate VM-based workloads to Azure platform services * Monitor Azure running workloads with Azure Monitor and Log AnalyticsWHO THIS BOOK IS FORAnyone who wants to learn about different Azure architectures by going through hands-on exercises.Peter De Tender has more than 20 years’ experience in architecting and deploying Microsoft datacenter technologies. Since early 2012, he started shifting to cloud technologies (Office 365, Intune) and quickly jumped onto the Azure platform, working as cloud solution architect and trainer, out of his own company. Since September 2019, Peter moved into an FTE role within Microsoft Corp in the prestigious Azure Technical Trainer team, providing Azure readiness workshops to larger customers and partners across the globe.Peter was an Azure MVP for 5 years, a Microsoft Certified Trainer for more than 12 years, and is still actively involved in the community as speaker, technical writer, and author.You can follow Peter on twitter @pdtit and check his technical blog, 007ffflearning.CHAPTER 1: DIGITAL TRANSFORMATION OVERVIEWThis chapter provides an introduction to “digital transformation” and how public cloud environments like Azure can help with that. You learn about business benefits in moving to public cloud such as high availability, scalability, security, and governance.CHAPTER 2: AUTOMATING AZURE DEPLOYMENTS USING ARM TEMPLATESIn this chapter, you will learn the core concepts of automated deployments of Azure resources, using ARM Templates. Starting from a preconfigured set of templates allowing deploying the baseline of the hands-on exercises, you also learn about optimizing ARM templates for virtual machine (VM) configuration management using PowerShell Desired State Configuration and Azure VM custom script extensions.CHAPTER 3: PERFORMING AZURE ASSESSMENTSA successful cloud migration of existing on-premises workloads starts with performing proper assessments. Azure has several tools helping with this process, to identify virtual machine supportability, as well as web applications and SQL Server databases. This chapter guides readers through different assessment tools, reflecting in another hands-on exercise on how to effectively use them to prepare a lift-and-shift migration to Azure.Chapter 4: Deploying Azure SQL as a ServiceAfter performing the recommended assessments, this chapter will detail the aspects of deploying and running SQL Server database in an Azure SQL Platform as a service architecture. Starting from the different topologies available, such as Azure SQL Single Instance, Azure SQL Managed Instance, and Azure SQL Elastic Pools, we will also touch on the actual migration of a traditional VM-based SQL Server database to Azure SQL in this chapter.CHAPTER 5: DEPLOYING AND RUNNING WEB APPS IN AZURE APPLICATION SERVICESAzure App services is the overall service allowing for running web apps, mobile apps, API apps, and Azure Function apps. Going back to our original running web application, the goal of this chapter is migrating this workload to Azure Web Apps. Before performing the actual migration and deployment, you will learn about several core Web App capabilities and features, such as deployment slots, integrated backup, high availability architecture, and load balancing. The exercise in this chapter covers several situations, starting from a Visual Studio web deploy, simulating a greenfield deployment, as well as guiding you through a lift-and-shift migration process using Azure App Services Assessment tool.CHAPTER 6: CONTAINERIZING WEB APPLICATIONS USING DOCKERIn the previous chapters, you learned about running an existing two-tier workload to Azure Infrastructure as a Service (IaaS) as well as migrating to Platform as a Service (PaaS). In this chapter and the next, we reuse the same application architecture, but moving it into a containerized architecture. Starting from the basics of Docker, you will practice the base Docker commands, as well as get guided through the configuration parameters in a Dockerfile. Next, we will take you to the Azure services allowing for running Docker containers, such as Azure Container Registry, Azure WebApp for Containers, and Azure Container Instance.CHAPTER 7: DEPLOYING AND RUNNING CONTAINERIZED WORKLOADS IN AZURE KUBERNETES SERVICES (AKS)As you learned by now, Azure offers several container-supporting services. While they do a really good job in providing adequate performance, ease of use and nice integration with other Azure services, you might also consider running the containers in a Kubernetes environment for several reasons. Starting from the base characteristics of Kubernetes and how it differs from other Azure container-supporting services, you will learn how to deploy an AKS cluster, how to manage it with Kubectl, and how to run your containerized workloads. To experiment with the powers and intelligence of Kubernetes, you will also learn about the built-in scalability, high availability, and rolling upgrade features of AKS.CHAPTER 8: MANAGING AND MONITORING AKS USING AZURE MONITOR AND KUBERNETES DASHBOARDGiven the complexity of Azure Kubernetes Service’s architecture, having a monitoring tool available at hand is crucial for your business-critical workloads. Azure Kubernetes Service can be managed and monitored using the “Kubernetes” way, relying on the standard Kubernetes dashboard. This could be beneficial if you use Kubernetes in a multi-cloud environment. However, Azure also provides an extensive and powerful integration with Azure Monitor, using Azure Insights. This chapter will describe both methodologies, after which you will also deploy and use both of them in the practical in this chapter.CHAPTER 9: DEPLOYING AZURE WORKLOADS USING AZURE DEVOPS CI/CD PIPELINESThis chapter will take all covered deployment scenarios to the next level and introduce you to Azure DevOps. Building on the experiences from Visual Studio Team Services (VSTS) and Team Foundation Server (TFS), allowing developers and application management teams in deployment platform rollouts for +10 years, one can use Azure DevOps to build out an end-to-end deployment pipeline covering continuous integration (CI) and continuous deployment (CD). This chapter guides readers through the core components available in Azure DevOps, and reusing several of the earlier performed tasks, but now using a DevOps methodology.
Digitalisierung und Künstliche Intelligenz
Für jeden von uns ist heute die Frage wichtig, wie in Zukunft Menschen und Maschinen zum Wohle des Menschen zusammenarbeiten und welche Anforderungen an Menschen hierbei entstehen. Dieses essential bietet für Interessierte den Einstieg. Wenn wir die Entwicklung in geeignete Bahnen lenken, dürfen wir dieser auch gespannt entgegensehen: Dann wirken – verbunden mit KI – Achtsamkeit, Anstrengung, Aufklärung, Anleitung und auch ein Stück weit Abenteuer im positiven Sinne zusammen. Grundlagen zu Digitalisierung, Vernetzung und KI.- Anwendungsfelder und Herausforderungen beim Einsatz von KI.- Kompetenzanforderungen.
Practical Natural Language Processing with Python
Work with natural language tools and techniques to solve real-world problems. This book focuses on how natural language processing (NLP) is used in various industries. Each chapter describes the problem and solution strategy, then provides an intuitive explanation of how different algorithms work and a deeper dive on code and output in Python.Practical Natural Language Processing with Python follows a case study-based approach. Each chapter is devoted to an industry or a use case, where you address the real business problems in that industry and the various ways to solve them. You start with various types of text data before focusing on the customer service industry, the type of data available in that domain, and the common NLP problems encountered. Here you cover the bag-of-words model supervised learning technique as you try to solve the case studies. Similar depth is given to other use cases such as online reviews, bots, finance, and so on. As you cover the problems in these industries you’ll also cover sentiment analysis, named entity recognition, word2vec, word similarities, topic modeling, deep learning, and sequence to sequence modelling.By the end of the book, you will be able to handle all types of NLP problems independently. You will also be able to think in different ways to solve language problems. Code and techniques for all the problems are provided in the book.WHAT YOU WILL LEARN* Build an understanding of NLP problems in industry* Gain the know-how to solve a typical NLP problem using language-based models and machine learning* Discover the best methods to solve a business problem using NLP - the tried and tested ones* Understand the business problems that are tough to solve Who This Book Is ForAnalytics and data science professionals who want to kick start NLP, and NLP professionals who want to get new ideas to solve the problems at hand.Mathangi is a renowned data science leader in India. She has 11 patent grants and 20+ patents published in the area of intuitive customer experience, indoor positioning, and user profiles. She has 16+ years of proven track record in building world-class data science solutions and products. She is adept in machine learning, text mining, NLP technologies, and NLP tools. She has built data science teams across large organizations including Citibank, HSBC, and GE, and tech startups such as 247.ai, PhonePe, and Gojek. She advises start-ups, enterprises, and venture capitalists on data science strategy and roadmaps. She is an active contributor on machine learning to many premier institutes in India. She is recognized as one of “The Phenomenal SHE” by the Indian National Bar Association in 2019.Chapter 1: Text Data in Real WordChapter Goal: This chapter focuses on various types of text data. The information it offers and the commercial value that each of the data could potentially offer. Understanding of the data provides the reader the landscape that they are getting intoNo of pages: 10Sub -Topics* NLP* Search * Reviews* Tweets/FB Posts* Chat data* SMS data* Content data* IVR utterance dataChapter 2: NLP in Customer ServiceChapter Goal: Case studies for problems in customer service and how they could be solved.No of pages: 39Sub - Topics1. A quick overview of the customer service industry2. Voice Calls3. Chats.4. Tickets Data5. Email Data6. Voice of customer analysis7. Intent Mining8. NPS/CSAT drivers9. Insights in Sales Chats10. Reasons for non purchase11. Survey Comment Analysis12. Mining Voice transcriptsChapter 3: NLP in Online ReviewsChapter Goal: Case studies for problems in online reviews and how they could be solved.No of pages: 39Sub - Topics:1. Sentiment Analysis2. Emotion Mining3. Approach 1 :Lexicon based approach4. Approach 2 : Rules based approach5. Approach 3 - Machine Learning based approach (Neural Network)6. Attribute ExtractionChapter 4: NLP in BFSIChapter Goal: case studies for problems in the banking industrySub - Topics:1. NLP in Fraud2. Method 1 (For extracting NER, popular libraries)3. Method 2 (For extracting NER, rules based approach)4. Method 3 (Classifier based approach using word embeddings and neural networks)5. Other use cases of NLP in BFSI6. Natural Language Generation in banksNo of pages: 47Chapter 5: NLP in Virtual AssistantsChapter Goal: Case study in building state of the art natural language botsSub- Topics1. Overview2. Approach 1 : The “Classic” approach using LSTMs3. Approach 2 : Generating Responses4. BERT5. Further nuances in building conversational bots:No of pages: 43
AR and VR Using the WebXR API
Gain an in-depth knowledge in immersive web development to create augmented reality (AR) and virtual reality (VR) applications inside web browsers using WebXR API, WebGL, Three.js, and A-Frame. This project-based book will provide the practice and portfolio content to make the most of what the futures of spatial computing and immersive technology have to offer.Beginning with technical analysis of how web browsers function, the book covers programming languages such as WebGL, JavaScript, and HTML, with an eye on a complete understanding of the WebXR lifecycle. You'll then explore how contemporary web browsers work at the code level and see how to set up a local development server and use it with the Visual Studio Code IDE to create 3D animation in the WebGL programming language.With a familiarity of the web-rendering pipeline in place, you’ll venture on to WebGL abstractions such as the Three.js JavaScript library and Mozilla’s A-Frame XR Framework, which use WebXR to create high-end visual effects. In the final projects of the book, you’ll create an augmented reality web session for an Android phone device, and create a VR scene in A-Frame (built on Three.js) to demo essential components of the WebXR API pertaining to user positioning and interaction.Game engines have become common-place for the creation of mixed reality content. However, developers not interested in learning entirely new workflows may be better suited to work within a medium almost universally open to all—the web; AR and VR Using the WebXR API will show you the way.WHAT YOU'LL LEARN* Master the creation of virtual reality and augmented reality features for web page* Prepare to work as an immersive web developer with a portfolio of projects in sought-after technologies* Review the fundamentals of writing shaders in WebGL* Experience the unity between client, server, and cloud architecture as it applies to location-based ARWHO THIS BOOK IS FORAspiring immersive web developers and developers already familiar with the fundamentals of web development who want to further explore topics such as spatial computing, computer vision, spatial anchors, and cloud-computing for multi-user social experiences. Rakesh Baruah is a writer and creator with 15 years of experience in new media, film, and television in New York City. After completing an MFA in screenwriting and directing for film from Columbia University, Rakesh joined the writers’ room of a hit, primetime, network drama as an assistant. The experience opened his eyes to the limits of television and the opportunities promised by 3D, immersive content. In 2016 he began a self-guided journey toward mixed reality design that has taken him through startups, bootcamps, the Microsoft offices, and many, many hours in front of a computer. He is the author of one previous book on virtual reality and the Unity Game Engine and has received an Nvidia-certified nanodegree in Computer Vision. He shares what he’s learned with you in a style and format designed specifically for the person who, in high school, preferred English class to Trigonometry. Chapter 1: IntroductionSub-Topics:- The Components of WebXR• Pose tracking• Camera data• Scene understanding- Hit-Testing- Anchors- Point-clouds- Surfaces- light-estimation• The webXR API- WebGL 1 → WebGL 2 → WebGPU → WebVR → WebXR- Khronos Group and WC3• The webXR emulator• Industry Standard XR Guidelines (Microsoft, Google)Chapter 2: SetupSub-Topics:- Types of Browsers and Requirements- Chrome Canary- Firefox Reality- Oculus Browser• How to setup a local server for development- Node, Python, Servez• Local machine setup- Download and install Visual Studio Code- Create GitHub account• Playgrounds vs. Local development while executive the code in the bookChapter 3: Introduction to Web BrowsersSub-Topics:• The Workings of the World Wide Web- Client - Server relationship- HTML, CSS, and Javascript• The Workings of a Web Page- The Document Object Model- The Render Engine- HTML5 and Canvas• Toward Native Code in the Browser- WebAssemblyPhysics and the GPUChapter 4: A Brief Introduction to WebGLSub-Topics:• The Big Picture of WebGL- A Crash Course in 3D Graphics- The Graphics Rendering → Rasterizing Pipeline• The Difference Between WebGL and JavaScript- CPU vs GPU- Browser vs Native- The Value of Many Threads• The Components of a WebGL Application- Vertex and Fragment Shaders- Uniforms, Attributes, and Buffers- ViewMatrix, ProjectionMatrix, and the WebGL Matrix Math Library• The Cognitive Dissonance between WebGL and Web ProgrammersChapter 5: WebXR Libraries -- Three.jsSub-Topics:• An Overview of JavaScript Libraries• Introduction to Three.js, which Makes Programming WebGL Easier• Async and Await vs Promises in JavaScript• JavaScript and the GPUChapter 6: WebXR Frameworks: Mozilla’s A-FrameSub-Topics:• A-Frame makes Three.js easier• The Components of A-Frame:- Scenes, Cameras, Objects, Interactions- Light and Shadows- 3D Objects and the gLTF file formatChapter 7: WebXR Engines: Babylon.jsSub-Topics:• TypeScript vs JavaScript- Type safety- Parallel Processing• The Babylon.js Tools- Playground- Inspector- Node Creator• What Makes an Engine vs. a Framework?- The role of physics in XR creationChapter 8: Web Augmented Reality in Chrome CanarySub-Topics:• An Overview of the WebXR Features in the Chrome Canary XR API- Hit-Testing- Camera access• Accessing Developer Features in Chrome• The Browser and Hardware Connection- Final Project: Client-Server database connection for data persistence in ARChapter 9: The Future of WebXRSub-Topics:• Computer Vision and WebXR- Facial Recognition and Filters• Multi-user Interaction- Spatial / Cloud Anchors- Social XR• Hand Gestures and Voice Commands- Motion Tracking• Cloud-Computing and Privacy- The ethical responsibility of the Immersive Web developer
Kubernetes
Master all the concepts and tools necessary to start administering a Kubernetes cluster and deploying applications to production. You will cover the entire curricula of the two Kubernetes certifications (for application developers and administrators).The initial chapters guide you through deployment of a Kubernetes cluster on virtual machines and explore the different components of the control plane. Next, you will work with the kubectl command-line tool; namespaces, labels, selectors, and annotations—common resources used through the Kubernetes API. The following chapters describe the principle of controllers and detail how workload controllers work as well as the possibilities for configuring deployed applications.You will also learn how to deploy a scalable and self-healing application, how pods are scheduled to nodes, how parts of the application can communicate, and how the application is discoverable from the outside. Next, you will cover security concerns describing the different authentication methods, the RBAC authorization mode, security contexts, network policies, and how to secure container images. You will also cover using persistent volumes for your containers to store long-term data, monitoring your clusters and applications and implementing design patterns for multi-container pods. The concluding chapters guide you through the upgrade of your deployed cluster.After reading this book, you will have enough knowledge to deploy a complex application using a Kubernetes cluster and be ready for the certification exams.WHAT YOU WILL LEARN* Deploy a Kubernetes cluster with kubeadm and learn how the control plane works* Discover how the Kubernetes API is structured* Deploy secure, auto-scaled, and self-healing applications* Master the kubectl command-line toolWHO THIS BOOK IS FORAdministrators and application developers with good knowledge of micro-services development and deployment.Philippe Martin has been working with Kubernetes for three years, first by creating an operator to deploy video CDNs into the cloud, later helping companies deploy their applications into Kubernetes. Philippe passed the CKAD certification about a year ago and the CKA certification recently.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.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.Chapter 1: Creating a Cluster with kubeadm• Provisioning Compute Resources• Install Docker on the hosts• Install kubeadm, kubelet, and kubectl on the hosts• Initialize the control plane node• Join the workersChapter 2: Control Plane Components• Explore the Control Plane servicesChapter 3: Accessing the Cluster• Install kubectl on your dev machine• Access the cluster from the dev machineChapter 4: Kubernetes Resources• Namespaces• Labels and selectors• AnnotationsChapter 5: The Workloads• Pod specs• Container specs• Pod controllers• ReplicaSet controller• Deployment controller• Update and rollback• Deployment strategiesChapter 6: Configuring Applications• Arguments to the command• Environment variables• Configuration file from ConfigMap• Configuration file from Secret• Configuration file from Pod fields• Configuration file from container resources fields• Configuration file from different sourcesChapter 7: Scaling an Application• Manual scaling• Auto-scalingChapter 8: Application Self-Healing• Controller to the rescue• Liveness probes• Resource limits and quality of service classesChapter 9: Scheduling Pods• Using label selectors to schedule pods on specific nodes• DaemonSets• Static pods• Resource requests• Running multiple schedulersChapter 10: Discovery and Load Balancing• Services• Services types• IngressChapter 11: Security• Authentication• Authorization• Security contexts• Network policies• Working with private Docker registriesChapter 12: Storage• Persistent volumes• Claiming a persistent volume• Using auto-provisioned persistent volumesChapter 13: Monitoring and Logging• Basic loggingChapter 14: Upgrading the Cluster• Upgrade the controller• Upgrade the workers• Upgrading the operating system• Backup a cluster• Restore a clusterChapter 15: kubectl• Managing kubeconfig file• Generic commands• Creating applications resources• Managing clusters• Getting documentationA. Curriculum CKAB. Curriculum CKAD
Foundation Gatsby Projects
Enhance your Gatsby skillset by building a series of ready-to-use web sites. With the aid of four projects, this book teaches you how to use Gatsby alongside the latest technologies, including Contentful, Twillio, and Stackbit.In the first project, you will create a simple agency site with a contact form and deploy it to Netlify. You'll then quickly be able to create other basic client sites. Next, you will learn to set up a blog site using Stackbit and Dev CMS. Other projects include a large site built with Contentful and a video chat using Twilio.Many Gatsby tutorials out there today only cover how to create blog sites – get ahead of the crowd using this book today.WHAT YOU'LL LEARN* Use Contentful CMS with Gatsby* Build sites quickly with Stackbit service* Develop a video chat site similar to Skype with Twilio services * Deploy all sites in Netlify* Add functionalities with the powerful Gatsby plugin ecosystem * Integrate advertisementsWHO THIS BOOK IS FORAnyone who wants to create a site using Gatsby. A little knowledge of React is expected but is not a necessity. You will need to be familiar with JavaScript concepts and be confident with basic web development.NABENDU BISWAS is a full stack JavaScript developer who has been working in the IT industry for the past 15 years and has worked for some of the world’s top development firms and investment banks. He is a passionate tech blogger who publishes on dev.to and medium.com and on thewebdev.tech. He is an all-round nerd, passionate about everything JavaScript, React and Gatsby. You can find him on Twitter @nabendu82.Chapter One-Agency SiteThe SetupBasic StylesSectionsWork and About PageDeploying SiteChapter Two-Blog Site using StackbitThe SetupDomain AddGatsby PluginsAdding AdvertisementsChapter Three-Tourism site with Contentful - Part OneThe SetupNavbar and FooterSimpleHero ComponentAbout SectionHot Tips SectionDeploy SiteImage OptimizationPage TransitionContact FormContentful SetupPlaces ComponentBlogComponentPhotos ComponentGatsby PluginsAdd AdvertisementsChapter Four-Tourism site with Contentful - Part TwoChapter Five-Tourism site with Contentful - Part ThreeChapter Six-Tourism site with Contentful - Part FourChapter Seven-Video Chat SiteThe SetupTwilio FunctionThe CodeVideo ImplementationCSS Changes