Allgemein
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
Systematische Steigerung der Energieeffizienz im Karosseriebau
Die vorliegende Dissertation präsentiert ein Konzept zur Steigerung der Energieeffizienz im Karosseriebau um durchschnittlich 10-15%. Die dafür benötigte Energietransparenz wird durch die strukturierte energetische Analyse bestehender Karosseriebauanlagen erreicht. Weiterhin besteht bereits im Karosseriebauplanungsprozess die Möglichkeit einer Energieprognose der zu planenden Arbeitsgruppen als auch des energetischen Lastprofils. In Abhängigkeit der energetischen Bewertung werden mit Hilfe eines Expertensystems entsprechend zu ergreifende Maßnahmen dem Planer zur Verfügung gestellt.Einleitung.- Grundlagen und Stand der Technik.- Stand der Forschung.- Konzeptentwicklung.- Anwendung des Gesamtkonzeptes am Beispiel des Karosseriebaus.- Zusammenfassung und Ausblick.
Applied Neural Networks with TensorFlow 2
Implement deep learning applications using TensorFlow while learning the “why” through in-depth conceptual explanations.You’ll start by learning what deep learning offers over other machine learning models. Then familiarize yourself with several technologies used to create deep learning models. While some of these technologies are complementary, such as Pandas, Scikit-Learn, and Numpy—others are competitors, such as PyTorch, Caffe, and Theano. This book clarifies the positions of deep learning and Tensorflow among their peers.You'll then work on supervised deep learning models to gain applied experience with the technology. A single-layer of multiple perceptrons will be used to build a shallow neural network before turning it into a deep neural network. After showing the structure of the ANNs, a real-life application will be created with Tensorflow 2.0 Keras API. Next, you’ll work on data augmentation and batch normalization methods. Then, the Fashion MNIST dataset will be used to train a CNN. CIFAR10 and Imagenet pre-trained models will be loaded to create already advanced CNNs.Finally, move into theoretical applications and unsupervised learning with auto-encoders and reinforcement learning with tf-agent models. With this book, you’ll delve into applied deep learning practical functions and build a wealth of knowledge about how to use TensorFlow effectively.WHAT YOU'LL LEARN* Compare competing technologies and see why TensorFlow is more popular* Generate text, image, or sound with GANs* Predict the rating or preference a user will give to an item* Sequence data with recurrent neural networksWHO THIS BOOK IS FORData scientists and programmers new to the fields of deep learning and machine learning APIs.ORHAN GAZI YALÇIN is a joint Ph.D. candidate at the University of Bologna & the Polytechnic University of Madrid. After completing his double major in business and law, he began his career in Istanbul, working for a city law firm, Allen & Overy, and a global entrepreneurship network, Endeavor. During his academic and professional career, he taught himself programming and excelled in machine learning. He currently conducts research on hotly debated law & AI topics such as explainable artificial intelligence and the right to explanation by combining his technical and legal skills. In his spare time, he enjoys free-diving, swimming, exercising as well as discovering new countries, cultures, and cuisines.Chapter 1: Introduction* How to Make the Most out of this Book* What is Tensorflow?* What’s New in Tensorflow 2.0* Google Colab and Jupyter Notebook* Installation and Environment SetupChapter 2: Machine Learning● What is Machine Learning?● Types of Machine Learninga. Supervised Learning: Regression, Classification (Binary or Multiclass)b. Unsupervised Learningc. Semi-Supervised Learningd. Reinforcement Learning● Machine Learning Terms:a. Data and Datasets: Train, Test, and Validationb. Cross-Validationc. Overfittingd. Bias & Variance,e. Fine-Tuningf. Performance Terms: Accuracy, Recall, Precision, F1 Score, Confusion Matrix● Introduction to and Comparison of ML Models:a. Regression (Linear and Logistic), Decision Trees, K-Nearest Neighbors, SupportVector Machines, K-Means Clustering, Principal Component Analysis● Steps of Machine Learning: Data Cleaning, Model Building, Dataset Split: Training, Testing,and Validation, and Performance EvaluationChapter 3: Deep Learning● Introduction to Deep Learning● Introduction to Perceptron● Activation Functions● Cost (Loss) Function● Gradient Descent Backpropagation● Normalization and Standardization● Loss Function and Optimization Functions● OptimizerChapter 4: Relevant Technologies Used for Machine Learning● Numpy● Matplotlib● Pandas● Scikit Learn● Deployment with FlaskChapter 5: TensorFlow 2.0● Tensorflow vs. Other Deep Learning Libraries● Keras API vs. Estimator● Keras API Syntax● Hardware Options and Performance Evaluation: CPUs vs. GPUs vs. TPUsChapter 6: Artificial Neural Networks (ANNs)● Introduction to ANNs● Perceptron Model● Linear (Shallow) Neural Networks● Deep Neural Networks● ANN Application Example with TF 2.0 Keras APIChapter 7: Convolutional Neural Networks (CNNs)● Introduction to CNN Architecture● CNN Basics: Strides and Filtering● Dealing with Image Data● Batch Normalization● Data Augmentation● CNN for Fashion MNIST with TF 2.0 Keras API● CNN for CIFAR10 with TF 2.0 Keras API (Pre-Trained Model)● CNN with Imagenet with TF 2.0 Keras API (Pre-Trained Model)Chapter 8: Recurrent Neural Networks (RNNs)● Introduction to RNN Architectures● Sequence Data (incl. Time Series)● Data Preparation● Simple RNN Architecture● Gated Recurrent Unit (GRU) Architecture● Long-Short Term Memory (LSTM) Architecture● Simple RNN, GRU, and LSTM ComparisonChapter 9: Natural Language Processing (RNN and CNN applications)● Introduction to Natural Language Processing● Text Processing● NLP Application with RNN● NLP Application with CNN● Text GenerationChapter 10: Recommender Systems● Introduction to Recommender Systems● Recommender System Using MovieLens Dataset● Recommender System Using Jester DatasetChapter 11: Auto-Encoders● Introduction to Auto-Encoders● Dimensionality Reduction● Noise Removal● Auto-Encoder for ImagesChapter 12: Generative Adversarial Networks (GANs)● Introduction to Generative Adversarial Networks● Generator and Discriminator Structures● Image Generation with GANs● Text Generation with GANsChapter 13: Conclusion
Games and Ethics
The number of digital gamers is increasing worldwide, but public debates about digital games commonly focus on questionable game content or problematic gaming behavior. This book offers a broader ethical perspective on digital game cultures, presenting theoretical and empirical work on the ethical dimensions of the development, production and distribution of digital games, as well as issues relating to responsible gaming and the pedagogical use of digital games. Questions of the communicative-cultural change in game cultures are linked with questions of media education and media ethics. With such a comprehensive approach, the volume promotes ethical discourse on digital game cultures.
Hyperparameter Optimization in Machine Learning
Dive into hyperparameter tuning of machine learning models and focus on what hyperparameters are and how they work. This book discusses different techniques of hyperparameters tuning, from the basics to advanced methods.This is a step-by-step guide to hyperparameter optimization, starting with what hyperparameters are and how they affect different aspects of machine learning models. It then goes through some basic (brute force) algorithms of hyperparameter optimization. Further, the author addresses the problem of time and memory constraints, using distributed optimization methods. Next you’ll discuss Bayesian optimization for hyperparameter search, which learns from its previous history.The book discusses different frameworks, such as Hyperopt and Optuna, which implements sequential model-based global optimization (SMBO) algorithms. During these discussions, you’ll focus on different aspects such as creation of search spaces and distributed optimization of these libraries.Hyperparameter Optimization in Machine Learning creates an understanding of how these algorithms work and how you can use them in real-life data science problems. The final chapter summaries the role of hyperparameter optimization in automated machine learning and ends with a tutorial to create your own AutoML script.Hyperparameter optimization is tedious task, so sit back and let these algorithms do your work.WHAT YOU WILL LEARN* Discover how changes in hyperparameters affect the model’s performance.* Apply different hyperparameter tuning algorithms to data science problems* Work with Bayesian optimization methods to create efficient machine learning and deep learning models* Distribute hyperparameter optimization using a cluster of machines* Approach automated machine learning using hyperparameter optimizationWHO THIS BOOK IS FORProfessionals and students working with machine learning.Tanay is a deep learning engineer and researcher, who graduated in 2019 in Bachelor of Technology from SMVDU, J&K. He is currently working at Curl Hg on SARA, an OCR platform. He is also advisor to Witooth Dental Services and Technologies. He started his career at MateLabs working on an AutoML Platform, Mateverse. He has worked extensively on hyperparameter optimization. He has also delivered talks on hyperparameter optimization at conferences including PyData, Delhi and PyCon, India.* Chapter 1: HyperparametersChapter Goal: To introduce what hyperparameters are, how they can affect themodel training. Also gives an intuition of how hyperparameter affects general machinelearning algorithms, and what value should we choose as per the training dataset.Sub - Topics1. Introduction to hyperparameters.2. Why do we need to tune hyperparameters3. Specific algorithms and their hyperparameters4. Cheatsheet for deciding Hyperparameter of some specific Algorithms.Chapter 2: Brute Force Hyperparameter TuningChapter Goal: To understand the commonly used classical hyperparameter tuningmethods and implement them from scratch, as well as use the Scikit-Learn library to do so.Sub - Topics:1. Hyperparameter tuning2. Exhaustive hyperparameter tuning methods3. Grid search4. Random search5. Evaluation of models while tuning hyperparameters.Chapter 3: Distributed Hyperparameter OptimizationChapter Goal: To handle bigger datasets and a large number of hyperparameterwith continuous search spaces using distributed algorithms and distributedhyperparameter optimization methods, using Dask Library.Sub - Topics:1. Why we need distributed tuning2. Dask dataframes3. IncrementalSearchCVChapter 4: Sequential Model-Based Global Optimization and Its HierarchicalMethodsChapter Goal: A detailed theoretical chapter about SMBO Methods, which usesBayesian techniques to optimize hyperparameter. They learn from their previous iterationunlike Grid Search or Random Search.Sub - Topics:1. Sequential Model-Based Global Optimization2. Gaussian process approach3. Tree-structured Parzen Estimator(TPE)Chapter 5: Using HyperOptChapter Goal: A Chapter focusing on a library hyperopt that implements thealgorithm TPE discussed in the last chapter. Goal to use the TPE algorithm to optimizehyperparameter and make the reader aware of how it is better than other methods.MongoDB will be used to parallelize the evaluations. Discuss Hyperopt Scikit-Learn and Hyperas with examples.1. Defining an objective function.2. Creating search space.3. Running HyperOpt.4. Using MongoDB Trials to make parallel evaluations.5. HyperOpt SkLearn6. HyperasChapter 6: Hyperparameter Generating Condition Generative Adversarial NeuralNetworks(HG-cGANs) and So Forth.Chapter Goal: It is based on a hypothesis of how, based on certain properties of dataset, one can train neural networks on metadata and generate hyperparameters for new datasets. It also summarizes how these newer methods of Hyperparameter Tuning can help AI to develop further.Sub - Topics:1. Generating Metadata2. Training HG-cGANs3. AI and hyperparameter tuning
Traefik API Gateway for Microservices
Use Traefik as a load balancer or a reverse proxy for microservices-based architecture. This book covers Traefik integration for microservices architecture concerns such as service discovery, telemetry, and resiliency.The book focuses on building an in-depth understanding of Traefik. It starts with the fundamentals of Traefik, including different load balancing algorithms available, and failure handling for application resiliency. Examples are included for the failure scenarios. TLS support is explained, including scenarios of TLS termination and TLS forwarding. Traefik supports TLS termination using Let's Encrypt. Traefik deployment in prominent microservices ecosystems is discussed, including Docker and Kubernetes.Traefik is a language-neutral component. This book presents examples of its deployment with Java-based microservices. The examples in the book show Traefik integration with Jaeger/Zipkin, Prometheus, Grafana, and FluentD. Also covered is Traefik for Python-based services and Java-based services deployed in the Kubernetes cluster. By the end of the book, you will confidently know how to deploy and integrate Traefik into prominent microservices ecosystems.WHAT YOU WILL LEARN* Understand Traefik basics and its components* Explore different load balancing scenarios and TLS termination* Configure service discovery, circuit breakers, timeouts, and throttling* Monitor Traefik using Prometheus and request tracingWHO THIS BOOK IS FORDevelopers and project managers who have developed microservices and are deploying them in cloud and on-premise environments with Kubernetes or Docker. The book is not specifically written for any particular programming language. The examples presented use Java or Python.RAHUL SHARMA is a seasoned Java developer with over 15 years of industry experience. In his career he has worked with companies of various sizes from enterprises to startups. During this time he has developed and managed microservices on the cloud (AWS/GCE/DigitalOcean) using open source software. He is an open source enthusiast and shares his experience at local meetups. He co-authored Java Unit Testing with JUnit 5 (Apress) and Getting Started with Istio Service Mesh (Apress).AKSHAY MATHUR is a software engineer with 15 years of experience, mostly in Java and web technologies. Most of his career has been spent building B2B platforms for enterprises, dealing with concerns such as scalability, configurability, multi-tenancy, and cloud engineering. He has hands-on experience implementing and operating microservices and Kubernetes in these ecosystems. Currently, he enjoys public speaking and blogging on new cloud native technologies (especially plain Kubernetes) and effective engineering culture.Chapter 1: Introduction to TraefikCHAPTER GOAL: THE CHAPTER COVERS THE NEED OF A BETTER LOAD BALANCER USING MICROSERVICES COMPONENTS. IT COVERS TRAEFIK COMPONENTS AND BUILD THE BASIC UNDERSTANDING. THE READER WILL SETUP THE ENVIRONMENT WHICH WILL GET STARTED WITH TRAEFIKNO OF PAGES: 20SUB -TOPICS1. Monolith to microservices architecture evolution1. Static configuration challenges2. Observability challenges3. TLS as identity2. Traefik components1. CLI2. DashboardChapter 2: Configure TraefikCHAPTER GOAL: THE CHAPTER WILL COVER ROUTING BASICS. IT WILL DISCUSS THE VARIOUS COMPONENTS.NO OF PAGES: 20SUB - TOPICS1. Entrypoint2. Routers3. ServicesChapter 3: Load Balancing and Failure DetectionCHAPTER GOAL: THE CHAPTER WILL COVER DIFFERENT LOAD BALANCING OPTIONS AVAILABLE IN TRAEFIK.NO OF PAGES : 30SUB - TOPICS:1. Configuring HTTP servicea. Round robinb. Weighted round robinc. Mirroringd. Health checks2. Configuring TCP servicea. Round robinb. Weighted round robinChapter 4: Configure TLSCHAPTER GOAL: TLS IS AN IMPORTANT PART OF LOAD BALANCING. WE WILL COVER HOW TO DO TLS TERMINATION AND TLS PASS THROUGH USING TRAEFIK.NO OF PAGES: 15SUB - TOPICS:1. Configure TLS terminationa. Using lets encrypt2. Configure TLS pass-throughChapter 5: Logs, Request Tracing and Black ListingCHAPTER GOAL: THE CHAPTER WILL COVER OBSERVABILITY FEATURES OF TRAEFIKNO OF PAGES: 30SUB - TOPICS:1. Trafik logging2. Access logs3. Request tracing4. IP blacklisting5. MetricesChapter 6: Traefik as MicroservicesCHAPTER GOAL: THE CHAPTER WILL USE TRAEFIK FOR MICROSERVICES TRAFFIC ROUTING. IT WILL LOAD CONFIGURATION AND DISCOVER SERVICES FROM A BACKEND. IT WILL CONFIGURE CIRCUIT BREAKERS, THROTTLING AND RETRIES.NO OF PAGES: 30SUB - TOPICS:1. Routing using service discovery2. configure circuit breakers and retries3. configure throttling4. Supporting canary routesChapter 7: Traefik as Kubernetes IngressCHAPTER GOAL: THE CHAPTER WILL SETUP TRAEFIK AS KUBERNETES INGRESS. IT WILL SETUP MUTUAL TLS AUTHENTICATION FOR IDENTITY AND ROLE BASED ACCESS CONTROL. IT WILL SEND METRICES AND TRACING TO PROMETHEUS AND JAGGER K8S COMPONENTS.NO OF PAGES: 30SUB - TOPICS:1. Configure Kubernetes ingress2. Enable mTLS authenticationa. configure RBAC3. Configure TLS termination for user requests4. Configure request tracing with Jaeger5. Capture metrices in prometheus
Machine Learning for Economics and Finance in TensorFlow 2
Machine learning has taken time to move into the space of academic economics. This is because empirical research in economics is concentrated on the identification of causal relationships in parsimonious statistical models; whereas machine learning is oriented towards prediction and is generally uninterested in either causality or parsimony. That leaves a gap for students, academics, and professionals who lack a standard reference on machine learning for economics and finance.This book focuses on economic and financial problems with an empirical dimension, where machine learning methods may offer something of value. This includes coverage of a variety of discriminative deep learning models (DNNs, CNNs, LSTMs, and DQNs), generative machine learning models (GANs and VAEs), and tree-based models. It also covers the intersection of empirical methods in economics and machine learning, including regression analysis, natural language processing, and dimensionality reduction.TensorFlow offers a toolset that can be used to define and solve any graph-based model, including those commonly used in economics. This book is structured to teach through a sequence of complete examples, each framed in terms of a specific economic problem of interest or topic. This simplifies otherwise complicated concepts, enabling the reader to solve workhorse theoretical models in economics and finance using TensorFlow.WHAT YOU'LL LEARN* Define, train, and evaluate machine learning models in TensorFlow 2* Apply fundamental concepts in machine learning, such as deep learning and natural language processing, to economic and financial problems * Solve theoretical models in economicsWHO THIS BOOK IS FORStudents, data scientists working in economics and finance, public and private sector economists, and academic social scientistsISAIAH HULL received his PhD in Economics from Boston College in 2013 and has since worked in the Research Division at Sweden’s Central Bank. He has published numerous articles in academic journals primarily concentrated in computational economics with applications in macroeconomics, finance, and housing. Most of his recent work makes use of techniques from machine learning. He also regularly presents at conferences on machine learning and big data in economics. And Isaiah is an accomplished teacher with experience teaching TensorFlow 2.0. Currently, he’s working on a project to introduce quantum computing to economists.Chapter 1: TensorFlow 2.0Chapter Goal: Introduce TensorFlow 2 and discuss preliminary material on conventions and practices specific to TensorFlow.· Differences between TensorFlow iterations· TensorFlow for economics and finance· Introduction to tensors· Review of linear algebra and calculus· Loading data for use in TensorFlow· Defining constants and variablesChapter 2: Machine Learning and EconomicsChapter Goal: Provide a high-level overview of machine learning models and explain how they can be employed in economics and finance. Part of the chapter will review existing work in economics and speculate on future use-cases.· Introduction to machine learning· Machine learning for economics and finance· Unsupervised machine learning· Supervised machine learning· Regularization· Prediction· EvaluationChapter 3: RegressionChapter Goal: Explain how regression models are used primarily for prediction purposes in machine learning, rather than hypothesis testing, as is the case in economics. Introduce evaluation metrics and optimization routines used to solve regression models.· Linear regression· Partially-linear regression· Non-linear regression· Logistic regression· Loss functions· Evaluation metrics· OptimizersChapter 4: TreesChapter Goal: Introduce tree-based models and the concept of ensembles.· Decision trees· Regression trees· Random forests· Model tuningChapter 5: Gradient BoostingChapter Goal: Introduce gradient boosting and discuss how it is applied, how models are tuned, and how to identify important features.· Introduction to gradient boosting· Boosting with regression models· Boosting with trees· Model tuning· Feature importanceChapter 6: ImagesChapter Goal: Introduce the high level Keras and Estimators APIs. Explain how these libraries can be used to perform image classification using a variety of deep learning models. Also, discuss the use of pretrained models and fine-tuning. Speculate on image classification uses in economics and finance.· Keras· Estimators· Data preparation· Deep neural networks· Convolutional neural networks· Recurrent neural networks· Capsule networks· Pretrained models· Model fine-tuningChapter 7: TextChapter Goal: Introduce text analysis, which has been applied extensively in economics. Cover the process of cleaning text and converting it into a numerical format, as well as a selection of unsupervised, supervised, and generative models. Discuss state-of-the-art models in the literature.· The natural language toolkit· Data cleaning and preparation· Tokenization· Word embeddings· The bag-of-words model· Sentiment analysis· Static and dynamic topic modeling· Text classification· Text generation· Pretrained modelsChapter 8: Time SeriesChapter Goal: Empirical work in macroeconomics and finance relies extensively on time series analysis. Methods from machine learning for sequential data analysis currently have low penetration in the economics literature. This chapter will speculate on how machine learning methods could be used in time series analysis.· Text and time series· Sequential models of machine learning· Recurrent neural networks· Long short-term memory· Forecasting· Model evaluation· Comparison with methods in economics and financeChapter 9: Dimensionality ReductionChapter Goal: Discuss dimensionality reduction as it is used in economics. Explain commonly used tools in machine learning for dimensionality reduction, including those which are also used in economics and finance.· Dimensionality reduction in economics· Principal component analysis· Partially linear regression· The autoencoder modelChapter 10: Generative ModelsChapter Goal: Introduce the concept of generative machine learning, including a discussion of existing models. Review the few applications of generative machine learning in economics and finance and speculate on potential future uses.· Introduction to generative machine learning· Variational autoencoders· Generative adversarial networks· Applications in economics and financeChapter 11: Theoretical ModelsChapter Goal: Discuss how theoretical models in economics and finance can be defined and solved using TensorFlow. Provide complete definitions and solutions for several workhorse models.· Defining mathematical models· Automatic differentiation· Optimizers· Performance evaluation· Solving models in economics and finance
Pro .NET 5 Custom Libraries
Leverage .NET 5, Microsoft’s bold new cross-platform implementation, for developing your very own cross-platform custom data types and libraries for Windows, Linux, and macOS.The book starts with the purpose and benefits of a custom cross-platform model of .NET data types and its architectural implementation in detail. Next, you will learn fundamental operations such as the equality and inequality operations in .NET 5, demonstrated with sample projects in C#. Implementation of comparison and sorting operations is discussed next followed by a discussion on cloning operations. Here you will learn details of overriding the clone virtual method and its implementation. Moving forward, you will understand custom formatting with specialized .NET data types in various functions and how to implement it. You will then go through .NET reference types along with developing a custom library for working with the software project. Finally, you will explore .NET 5 assemblies and modules followed by their APIs.After reading Pro .NET 5 Custom Libraries, you will be able to work on fundamental operations for productivity and quality in your designs of .NET 5 custom data types.WHAT YOU WILL LEARN* Work with .NET 5 assembliesWork with .NET 5 modules * Understand the logical and physical organization of .NET 5 modules* Implement custom .NET reference types from scratch* Implement a custom .NET value type from scratchWHO THIS BOOK IS FORSoftware developers working on .NET and .NET Core platform.ROGER VILLELA is a software engineer and entrepreneur with almost 30 years of experience in the industry and works as an independent professional. Currently, he is focused on his work as a book author and technical educator and specializes in the inner works of orthogonal features of the following Microsoft development platforms and specialized APIs:* Microsoft Windows operating system base services* Microsoft Windows APIs architecture and engineering* Microsoft Universal Windows Platform (UWP)* Microsoft WinRT platform* Microsoft .NET Framework implementation of the runtime environment (CLR)His works are based on Microsoft Windows SDK tools and libraries, Microsoft Visual Studio platform (Microsoft Windows), platform foundational APIs: architectures and engineering, and Microsoft Windows operating system using the following programming languages, extensions, and projections:* C/C++* Assembly (Intel IA-32/Intel 64 (x64/amd64))* Component extensions/projections for runtimes :* C++/CLI* C++/CX* C++/WinRT* C#* Common Intermediate Language (MSIL) implementation for CLR platformCHAPTER 1: IMPLEMENTING A CUSTOM .NET DATA TYPE FROM SCRATCH.CHAPTER GOAL: IN THIS CHAPTER WE WILL LEARN ABOUT THE PURPOSE AND BENEFITS OF A CUSTOM CROSS-PLATFORM MODEL OF .NET DATA TYPE, AND ABOUT THE IMPLEMENTATION ARCHITECTURE IN CUSTOM LIBRARIES.NO OF PAGES: 50-90SUB - TOPICS1. Acronym's.2. Architecture for implementation.3. Logical Organization.4. Data structures.5. Deriving from System.Object:1. Constructors.2. Implementing ReferenceEquals static method.3. Overriding ToString virtual method.4. Overriding Clone virtual method – first steps.5. Implementing MemberwiseClone protected method – first steps.6. Implementing others inherited methods.7. "Destructors".6. Sample projectsC# programming language.Custom Libraries.7. Do's and Don'ts.CHAPTER 2: IMPLEMENTING EQUALITY AND INEQUALITY.CHAPTER GOAL: IN THIS CHAPTER WE WILL LEARN ABOUT THE IMPLEMENTATION OF EQUALITY AND INEQUALITY OPERATIONS.NO OF PAGES: 50-90SUB - TOPICS1. Acronym's.2. Overriding Equals virtual method.3. Implementing the required operators.4. Implementing System.IEquatable interface.5. Sample projectsC# programming language.Custom Libraries.6. Do's and Don'ts.CHAPTER 3: IMPLEMENTING COMPARISON AND SORTING.CHAPTER GOAL: IN THIS CHAPTER WE WILL LEARN ABOUT THE IMPLEMENTATION OF COMPARISON AND SORTING OPERATIONS.NO OF PAGES: 50-90SUB - TOPICS1. Acronym's.2. Implementing System.IComparable and System.IComparable interfaces.3. Implementing the required operators.4. Sample projectsC# programming language.Custom Libraries.5. Do's and Don'ts.CHAPTER 4: IMPLEMENTING CLONING OPERATION.CHAPTER GOAL: IN THIS CHAPTER WE WILL LEARN ABOUT THE IMPLEMENTATION OF CLONING OPERATION.NO OF PAGES: 50-90SUB - TOPICS1. Acronym's.2. Working with clone operation.3. Overriding Clone virtual method – Details.4. Implementing MemberwiseClone protected method - Details.5. Sample projectsC# programming language.Custom Libraries.6. Do's and Don'ts.CHAPTER 5: IMPLEMENTING A CUSTOM FORMATTER.CHAPTER GOAL: IN THIS CHAPTER WE WILL LEARN ABOUT THE IMPLEMENTATION OF CUSTOM FORMATTING USING SPECIALIZED .NET DATA TYPES.NO OF PAGES: 50-90SUB - TOPICS1. Acronym's.2. Implementing the System.IFormattable .NET interface.3. Overriding System.Object.ToString virtual method.4. Working with System.IFormatProvider .NET interface.5. Working with System.ICustomFormatter .NET interface.6. Sample projectsC# programming language.Custom Libraries.7. Do's and Don'tsCHAPTER 6: WORKING WITH .NET VALUE TYPES.CHAPTER GOAL: IN THIS CHAPTER WE WILL LEARN ABOUT .NET SYSTEM.VALUETYPE THE IMPLEMENTATION OF A CUSTOM .NET VALUE TYPE AND THE DEVELOPMENT FOR A CUSTOM LIBRARY FOR WORKING WITH IN OUR SOFTWARE PROJECTS.NO OF PAGES : 50-90SUB - TOPICS:1. Acronym's.2. Implementing a .NET value type from scratch.3. The purpose of a .NET value type.4. Implementing the equality and inequality operations.5. Implementing comparisons and sorting operations.6. Implementing custom formatting.7. Implementing the required operators.8. Sample projectsC# programming language.Custom Libraries.9. Do's and Don'ts.CHAPTER 7: WORKING WITH .NET REFERENCE TYPES.CHAPTER GOAL: IN THIS CHAPTER WE WILL LEARN ABOUT .NET REFERENCE TYPE THE IMPLEMENTATION OF A CUSTOM .NET REFERENCE TYPE AND THE DEVELOPMENT FOR A CUSTOM LIBRARY FOR WORKING WITH IN OUR SOFTWARE PROJECTS.NO OF PAGES : 50-90SUB - TOPICS:1. Acronym's.2. Implementing a .NET reference type from scratch.3. The purpose of a .NET reference type.4. Implementing the equality and inequality operations.5. Implementing comparisons and sorting operations.6. Implementing custom formatting.7. Implementing the required operators.8. Sample projectsC# programming language.Custom Libraries.9. Do's and Don'ts.CHAPTER 8: WORKING WITH .NET INTERFACE TYPESCHAPTER GOAL: IN THIS CHAPTER WE WILL LEARN ABOUT .NET INTERFACE TYPE THE IMPLEMENTATION OF A CUSTOM .NET INTERFACE TYPE AND THE DEVELOPMENT FOR A CUSTOM LIBRARY FOR WORKING WITH IN OUR SOFTWARE PROJECTS.NO OF PAGES : 50-90SUB - TOPICS:1. Acronym's.2. Implementing a .NET interface type from scratch.3. The purpose of a .NET interface type.4. Implementing the equality and inequality operations.5. Implementing comparisons and sorting operations.6. Implementing custom formatting.7. Implementing the required operators.8. Sample projectsC# programming language.Custom Libraries.9. Do's and Don'ts.CHAPTER 9: WORKING WITH .NET ASSEMBLIES AND .NET MODULESCHAPTER GOAL: IN THIS CHAPTER WE WILL LEARN ABOUT THE .NET ASSEMBLIES AND .NET MODULES AND DEVELOPMENT OF A CUSTOM LIBRARY FOR WORKING WITH INFORMATION, AND THEIR USES IN OUR SOFTWARE PROJECTS.NO OF PAGES : 50-90SUB - TOPICS:1. Acronym's.2. Working with .NET Assembly.3. Working with .NET Module.4. Logical Organization.5. Physical organization.6. Data structures.7. .NET APIs for working with information about .NET Assemblies.8. .NET APIs for working with information about .NET Modules.9. Sample projectsC# programming language.Libraries.10. Conclusion.
Beginning Unreal Engine 4 Blueprints Visual Scripting
Discover how Unreal Engine 4 allows you to create exciting games using C++ and Blueprints. This book starts with installing, launching, and examining the details of Unreal Engine.Next, you will learn about Blueprints and C++ and how to leverage them. The following chapters talk in detail about gameplay, basic physics, and ray-casting for game development in Unreal Engine. Furthermore, you’ll create material, meshes, and textures.The last chapter brings all the concepts together by building a demo game. By the end of the book, you’ll be equipped with the know-how and techniques needed to develop and deploy your very own game in Unreal Engine.WHAT YOU WILL LEARN* Discover Blueprints and how to apply them in Unreal Engine 4* Get started with C++ programming in Unreal Engine 4* Apply the concepts of physics and ray-casting* Work with the Gameplay Framework WHO THIS BOOK IS FORBeginners interested in learning Blueprints visual scripting and C++ for programming games in Unreal Engine 4 would find this book useful.Satheesh Pv is a game programmer living in Mumbai, India. He started his career as a game developer in 2012 by making a first-person multiplayer game with his brother and close friend using Unreal Development Kit and created Unreal X-Editor, which was an IDE developed for UnrealScript, the native scripting language of Unreal Engine 3. He was selected by Epic Games as one of the closed beta testers for Unreal Engine 4 before its public release. He is also a moderator at Unreal Engine forums as well as a spotlight member and Engine contributor.CHAPTER 1: INTRODUCTION TO UNREAL ENGINE 4Chapter Goal: The reader is given a brief introduction to Unreal Engine 4 and how to get both binary version and source code version of the Engine. After installing the Engine, we will create a sample project from one of the given templates and learn about the Unreal Editor and its various settings.Sub -Topics1. Getting Unreal Engine by Epic Games Launcher2. Getting Unreal Engine from GitHub and compiling3. Getting to know more about Unreal EditorCHAPTER 2: INTRODUCTION TO BLUEPRINTSChapter Goal: This is an introduction to the visual scripting language of Unreal Engine 4 called Blueprints. The reader will learn about what are Blueprints, the various types of Blueprints, and how to create and use it in a game.Sub - Topics1. What are Blueprints?2. Blueprint types3. Creating a sample BlueprintCHAPTER 3: C++ AND UNREAL ENGINEChapter Goal: C++ is a powerful language, and in Unreal Engine 4, it is of no exception. In this chapter, we will go through the basics of Unreal C++ by creating C++ classes and accessing various properties and functions in Blueprint and communicating between these two powerful tools.Sub - Topics:1. Creating a new C++ class2. Exposing variables and functions to Blueprints3. Calling C++ functions in BlueprintsCHAPTER 4: GAMEPLAY FRAMEWORKChapter Goal: Introduction to various important gameplay classes that actually make a game. The reader will learn about how to get input from the player and show data to the user through HUD.Sub - Topics:1. Gameplay classes2. Creating character and controller classes to get input from player3. Show relevant data to the player through user interfaceCHAPTER 5: BASIC PHYSICS AND RAYCASTINGChapter Goal: Physics is one of the main driving forces behind any game. If you want to interact with an object in the world or to destroy something in the game world, you need raycasting and physics. In this chapter, the reader will learn how to raycast and pickup an item as well as shoot and destroy something in the world.Sub - Topics: 1. Physics and raycasting2. Using raycasting to pick up an item3. Using physics to destroy something in the game worldCHAPTER 6: IMPORTING MESHES, TEXTURES, AND CREATING MATERIALSChapter Goal: In this chapter, readers will be introduced to the concept of materials and how to create and use them as well as creating instances to modify the material quickly. The reader will also learn how to import a custom 3D models and textures.Sub - Topics:1. Importing meshes and textures2. Material types3. Creating material and material instances4. Modifying the material at runtime using Blueprints and C++CHAPTER 7: PROJECT: DEMO GAMEChapter Goal: Using all the above knowledge, we will create a sample game and package it.Sub - Topics:1. Sample game using Blueprints and C++
Blockchain
Wer noch nie über Blockchain gehört hat, würde bestimmt das Buch gerade nicht in der Hand halten. Das Thema ist heiß diskutiert und hat bereits viele Befürworter sowie Gegner. In diesem Buch erwartet Sie eine klare und verständliche Erklärung der Blockchain-Technologie mit ausführlichen Erläuterungen zu deren Entstehung, Technik und Umsetzung. Damit möchten wir die Debatte um Blockchain-Hype versachlichen und Ihnen die Entscheidung überlassen, ob Blockchain für Sie tatsächlich ein Hype oder eine Innovation ist. Christoph Meinel (Univ.-Prof., Dr. sc. nat., Dr. rer. nat., 1954) ist wissenschaftlicher Direktor und Geschäftsführer des Hasso-Plattner-Instituts für Digital Engineering gGmbH (HPI). Christoph Meinel ist ordentlicher Professor (C4) für Informatik und hat den Lehrstuhl für Internet-Technologien und Systeme am HPI inne. Seine besonderen Forschungsinteressen liegen in den Bereichen Internet- und Informationssicherheit und Digitale Bildung. Daneben ist er aktiv in der Innovationsforschung rund um die Stanforder Innovationsmethode des Design Thinking.Tatiana Gayvoronskaya ist seit März 2016 in der Forschung in den Bereichen Blockchain-Technologie, Identitätsmanagement und IT-Sicherheit am Hasso-Plattner-Institut für Digital Engineering gGmbH (HPI) tätig. Zusammen mit Prof. Dr. Christoph Meinel hat sie bereits im Juli 2018 einen MOOC auf OpenHPI-Plattform zum Thema Blockchain erarbeitet und durchgeführt.
Strategie, Planung und Organisation von Testprozessen
Das Buch gibt konkrete Tipps zur erfolgreichen Organisation von Softwaretests. Denn: Für erfolgreiche Testprojekte sind Planung und Konzeption im Vorfeld essentiell. Die richtigen Weichenstellungen verhindern von Anfang an Probleme und zeigen notwendige Handlungsbedarfe im Softwaretest auf. Dieses Werk zeigt neben theoretischen Grundlagen die Umsetzung in der Praxis auf und behandelt dabei typische Probleme. Frank Witte erläutert die entscheidenden Aspekte, die im Testkonzept zu berücksichtigen sind, um den Testprozess optimal zu unterstützen und zu begleiten.FRANK WITTE verfügt über langjährige Erfahrung im Softwaretest in unterschiedlichen Unternehmen und Branchen. Bei jedem neuen Softwareprojekt ist es für ihn erforderlich, Testaktivitäten umfassend zu planen und den Test zu organisieren. Daher hat er bereits mehrere Testkonzepte selbst verfasst und erfahren, worauf es dabei besonders ankommt und welche Probleme bereits im Vorfeld und am Beginn von Testprozessen erkannt, aber auch proaktiv verhindert oder verringert werden können.Testdokumente nach IEEE 829.- Teststrategie.- Testziele.- Testplanung.- Bezeichnung des Testkonzepts und Einleitung.- Testorganisation.- Prozessbeschreibung.-Testobjekte und Testphasen.-Teststufen.- Zu testende Leistungsmerkmale.-Leistungsmerkmale, die nicht getestet werden.-Priorisierung von Testfällen.-Permanente Testorganisation.-Abnahmekriterien .-Kriterien für Testabbruch und Testfortsetzung.-Testrisiken.-Testdaten.-Testdokumentation.-Testaufgaben.-Testumgebung.-Verantwortlichkeiten, Zuständigkeiten und Kommunikation.-Personal, Einarbeitung, Ausbildung.-Zeitplan/ Arbeitsplan.-Planungsrisiken und Unvorhersehbares.-Genehmigung und Freigabe.-Projektorganisation.-Testmethoden.-Reifegrad des Testmanagements.-Besonderheiten der Testorganisation in agilen Projekten.-Künstliche Intelligenz und kognitives Testen.
Practical Machine Learning with AWS
Successfully build, tune, deploy, and productionize any machine learning model, and know how to automate the process from data processing to deployment.This book is divided into three parts. Part I introduces basic cloud concepts and terminologies related to AWS services such as S3, EC2, Identity Access Management, Roles, Load Balancer, and Cloud Formation. It also covers cloud security topics such as AWS Compliance and artifacts, and the AWS Shield and CloudWatch monitoring service built for developers and DevOps engineers. Part II covers machine learning in AWS using SageMaker, which gives developers and data scientists the ability to build, train, and deploy machine learning models. Part III explores other AWS services such as Amazon Comprehend (a natural language processing service that uses machine learning to find insights and relationships in text), Amazon Forecast (helps you deliver accurate forecasts), and Amazon Textract.By the end of the book, you will understand the machine learning pipeline and how to execute any machine learning model using AWS. The book will also help you prepare for the AWS Certified Machine Learning—Specialty certification exam.WHAT YOU WILL LEARN* Be familiar with the different machine learning services offered by AWS * Understand S3, EC2, Identity Access Management, and Cloud Formation* Understand SageMaker, Amazon Comprehend, and Amazon Forecast* Execute live projects: from the pre-processing phase to deployment on AWSWHO THIS BOOK IS FORMachine learning engineers who want to learn AWS machine learning services, and acquire an AWS machine learning specialty certificationHIMANSHU SINGH is Technology Lead and Senior NLP Engineer at Legato Healthcare (an Anthem Company). He has seven years of experience in the AI industry, primarily in computer vision and natural language processing. He has authored three books on machine learning. He has an MBA from Narsee Monjee Institute of Management Studies, and a postgraduate diploma in Applied Statistics.Part-I – Introduction to Amazon Web Services (100 Pages)Chapter 1: AWS Concepts and TechnologiesIntroduction to services like S3, EC2, Identity Access Management, Roles, Load Balancer, Cloud Formation, etc.Chapter 2: AWS Billing and PricingUnderstanding AWS pricing, billing, group and tagging, etc.Chapter 3: AWS Cloud SecurityDescription about AWS compliance and artifacts, AWS Shield, Cloudwatch, Cloud Trail, etc.Part-II – Machine Learning in AWS (300 Pages)Chapter 4: Data Collection and PreparationConcepts include AWS data stores, migration and helper tools. It also includes pre-processing concepts like encoding, feature engineering, missing values removal, etc.Chapter 5: Data Modelling and AlgorithmsIn this section, we will talk about all the algorithms that AWS supports, including regression, clustering, classification, image, and text analytics, etc. We will then look at Sagemaker service and how to make models using it.Chapter 6: Data Analysis and VisualizationThis chapter talks about the relationship between variables, data distributions, the composition of data, etc.Chapter 7: Model Evaluation and OptimizationThis chapter talks about the monitoring of training jobs, evaluating the model accuracy, and fine-tuning models.Chapter 8: Implementation and OperationIn this chapter, we’ll look at the deployment of models, security, and monitoring.Chapter 9: Building a Machine Learning WorkflowIn this chapter, we’ll look at the machine learning workflow in AWS .Part-IV – Projects (100 Pages)Chapter 10: Project – Building skills with AlexaChapter 11: Project - Time series forecasting using Amazon forecastChapter 12: Project – Modelling and deployment using XGBoost in SagemakerChapter 13: Text classification using Amazon comprehend and textractChapter 14: Building a complete project pipeline
Pro Cryptography and Cryptanalysis
Utilize this comprehensive, yet practical, overview of modern cryptography and cryptanalysis to improve performance. Learn by example with source code in C# and .NET, and come away with an understanding of public key encryption systems and challenging cryptography mechanisms such as lattice-based cryptography.Modern cryptography is the lifeboat of a secure infrastructure. From global economies and governments, to meeting everyday consumer needs, cryptography is ubiquitous, and used in search, design, data, artificial intelligence, and other fields of information technology and communications. Its complexity can lead to misconfiguration, misuse, and misconceptions. For developers who are involved in designing and implementing cryptographic operations in their applications, understanding the implications of the algorithms, modes, and other parameters is vital.PRO CRYPTOGRAPHY AND CRYPTANALYSIS is for the reader who has a professional need or personal interest in developing cryptography algorithms and security schemes using C# and .NET. You will learn how to implement advanced cryptographic algorithms (such as Elliptic Curve Cryptography Algorithms, Lattice-based Cryptography, Searchable Encryption, Homomorphic Encryption), and come away with a solid understanding of the internal cryptographic mechanisms, and common ways in which the algorithms are correctly implemented in real practice. With the new era of quantum computing, this book serves as a stepping stone to quantum cryptography, finding useful connections between current cryptographic concepts and quantum related topics.WHAT YOU WILL LEARN* Know when to enlist cryptography, and how it is often misunderstood and misused* Explore modern cryptography algorithms, practices, and properties* Design and implement usable, advanced cryptographic methods and mechanisms* Understand how new features in C# and .NET impact the future of cryptographic algorithms* Use the cryptographic model, services, and System.Security.Cryptography namespace in .NET* Modernize your cryptanalyst mindset by exploiting the performance of C# and .NET with its weak cryptographic algorithms* Practice the basics of public key cryptography, including ECDSA signatures* Discover how most algorithms can be brokenWHO THIS BOOK IS FORInformation security experts, cryptologists, software engineers, developers, data scientists, and academia who have experience with C#, .NET, as well as IDEs such as Visual Studio, VS Code, or Mono. Because this book is for an intermediate to advanced audience, readers should also possess an understanding of cryptography (symmetric and asymmetric) concepts.MARIUS IULIAN MIHAILESCU, PHD is CEO of Dapyx Solution Ltd., a company focused on security- and cryptography-related research. He has authored and co-authored more than 50 articles, journal contributions, and conference proceedings, and three books related to security and cryptography. He lectures at well-known national and international universities, teaching courses on programming, cryptography, information security, and other technical topics. He holds a PhD (thesis on applied cryptography over biometrics data) and two MSc in information security and software engineering.STEFANIA LOREDANA NITA, PHD is a software developer and researcher at the Institute for Computers. Prior to that she was an assistant lecturer at the University of Bucharest, where she taught courses on advanced programming techniques, simulation methods, and operating systems. She has authored and co-authored more than 15 papers and journals, most recently Advanced Cryptography and Its Future: Searchable and Homomorphic Encryption, as well as two books. She holds a PhD (thesis on advanced cryptographic schemes using searchable encryption and homomorphic encryption), an MSc in software engineering and two BSc in computer science and mathematics.PART I: FOUNDATIONAL TOPICSChapter 1: Cryptography FundamentalsChapter 2: Mathematical Background and Its ApplicabilityChapter 3: Large Integer ArithmeticChapter 4: Floating-Point ArithmeticChapter 5: What's New in C# 8.0Chapter 6: Secure Coding GuidelinesChapter 7: .NET Cryptography ServicesChapter 8: Overview of System.Cryptography NamespaceChapter 9: Cryptography Libraries in C# and .NETPART II: CRYPTOGRAPHYChapter 10: Elliptic-Curve CryptographyChapter 11: Lattice-based CryptographyChapter 12: Searchable EncryptionChapter 13: Homomorphic EncryptionChapter 14: (Ring) Learning with Errors CryptographyChapter 15: Chaos-based CryptographyChapter 16: Big Data CryptographyChapter 17: Cloud Computing CryptographyPART III: PRO CRYPTANALYSISChapter 18: Getting Started with CryptanalysisChapter 19: Cryptanalysis Attacks and TechniquesChapter 20: Linear and Differential CryptanalysisChapter 21: Integral CryptanalysisChapter 22: AttacksChapter 23: Text CharacterizationChapter 24: Implementation and Practical Approach of Cryptanalysis Methods
Azure DevOps for Web Developers
Explore the architecture, product offerings, and the various stages of implementation processes in Azure DevOps. The book starts with the basic concepts of DevOps and moves on to discuss project management in Azure DevOps. Next, you will learn requirement management and version control in DevOps. Along the way, you will go through test management followed by continuous integration and build automation with more details on code quality and security implementations.Moving forward, you will learn release pipeline and infrastructure as code implementation including ARM-based environment provisioning and execution. Finally, you’ll cover DevOps architecture blueprints used for deploying your web applications to different platforms .After reading this book, you will be able to understand each stage of Azure DevOps and master its implementation.WHAT YOU WILL LEARN* Understand the various concepts of Azure DevOps* Apply DevOps concepts in a variety of application contexts including web applications, containers, and database* Understand the implementation of end-to-end DevOps in Azure* Work with the different DevOps design patterns and architectures in AzureWHO IS THIS BOOK FOR:Developers and architects working with Azure.For over a dozen years AMBILY has worked on cloud adoption and accelerating software delivery through DevOps. As the head of Azure, DevOps, and UI practice at TCS HiTech Industry she supports major public and private sector companies across the globe in their cloud journey and DevOps implementation. Ambily blogs about her experiences and speaks at conferences to share what she has learned.Blog at https://ambilykk.com/CHAPTER 1: DEVOPS BASICS AND VARIATIONSCovers the basic concepts of DevOps and how the journey or explain the maturity model of DevOps in an organization. This roughly cover the concepts like DevOps Team, DevOps Practices,DevOps Variations- DevOps 1.0, DevOps 2.0, SecDevOps and Intelligent DevOpsCHAPTER 2: PROJECT MANAGEMENT USING AZURE DEVOPSThis chapter talks about organization and project. Start with creation of Azure DevOps organization, user management, Security policies, permissions, Azure AD integration, etc. Then, step into a single project and explain project level permissions, areas, iterations, process, etc.CHAPTER 3: REQUIREMENT MANAGEMENT USING AZURE DEVOPSExplain the usage of different work items like Epic, features, product backlog, spring backlog, etc. How the requirements are tracked in the systemCHAPTER 4: VERSION CONTROL USING AZURE DEVOPSExplain the version control system, possibilities to integrate with external systems, how to work offline and online mode, etc. Branching and merging strategy followed by various teams.CHAPTER 5: TEST MANAGEMENT USING AZURE DEVOPSThis chapter focus of the Test plans which should be executed to verify the implementations.CHAPTER 6: CONTINUOUS INTEGRATION AND BUILD AUTOMATIONDiscuss about the concept of Continuous Integration with the help of web application and database project. Also, explain more about the code quality and security implementations in build configuration.CHAPTER 7: RELEASE PIPELINE AND CONTINUOUS DEPLOYMENTThis chapter focus on the release pipeline and Infrastructure as a code implementation. Covers ARM based environment provisioning, execution of automated test scripts, implementation of quality gates and approval flows, and release to various environments.CHAPTER 8: CONTINUOUS FEEDBACK AND OTHER FEATURESExplains the Integration of AppInsights back to the DevOps backlog, alert configurations, collaboration features.CHAPTER 9: DEVOPS ARCHITECTURE BLUEPRINTSThis chapter covers architecture blueprints for commonly used Azure product catalogs.CHAPTER 10: DEVOPS FOR SUPPORT TEAMThis chapter covers more about the Swarming support model and various architecture options.
Pro Microsoft Power BI Administration
Manage Power BI within organizations. This book helps you systematize administration as Microsoft shifts Power BI from a self-service tool to an enterprise tool. You will learn best practices for many Power BI administrator tasks. And you will know how to manage artifacts such as reports, users, work spaces, apps, and gateways. The book also provides experience-based guidance on governance, licensing, and managing capacities.Good management includes policies and procedures that can be applied consistently and even automatically across a broad user base. This book provides a strategic road map for the creation and implementation of policies and procedures that support Power BI best practices in enterprises. Effective governance depends not only on good policies, but also on the active and timely monitoring of adherence to those policies. This book helps you evaluate the tools to automate and simplify the most common administrative and monitoring tasks, freeing up administrators to provide greater value to the organization through better user training and awareness initiatives.WHAT YOU WILL LEARN* Recognize the roles and responsibilities of the Power BI administrator* Manage users and their work spaces* Know when to consider using Power BI Premium* Govern your Power BI implementation and manage Power BI tenants* Create an effective security strategy for Power BI in the enterprise* Collaborate and share consistent views of the data across all users* Follow a life cycle management strategy for rollout of dashboards and reports* Create internal training resources backed up by accurate documentation* Monitor Power BI to better understand risks and compliance manage costs, and track implementation WHO THIS BOOK IS FORIT professionals tasked with maintaining their corporate Power BI environments, Power BI administrators and power users interested in rolling out Power BI more widely in their organizations, and IT governance professionals tasked with ensuring adherence to policies and regulationsÁSGEIR GUNNARSSON is a data platform MVP and Chief Consultant at Datheos. He works on business intelligence solutions using the whole of the Microsoft BI stack. Ásgeir has been working in BI since 2007 both as a consultant and internal employee. Before turning to BI, he worked as a technical trainer and he currently teaches BI courses at the Continuing Education Department of the University of Iceland. Ásgeir speaks regularly at events both domestic and internationally and is the group leader of the Icelandic PASS Group as well as the Icelandic Power BI user group. He is passionate about data and loves solving problems with BI.MICHAEL JOHNSON is a data platform MVP from Johannesburg, South Africa where he works as a business intelligence architect. Outside of work, Michael runs the local SQL Server User Group and provides Power BI presentations and training both locally and abroad.PART I. GOVERNANCE1. Introduction to Governance and Governance Strategies2. Power BI Licensing3. Collaboration4. Laws and Policies5. Application Lifecycle Management6. Training7. DocumentationPART II. ADMINISTRATION8. Introduction to Power BI Administration9. Managing the Tenant10. Administering Power BI Capacities11. Workspace Administration12. Managing Users and Security13. Datasets & Dataflows14. On-premises Data Gateway15. Power BI Administration Tools16. Monitoring
Vorkurs Informatik für Dummies
Möchten Sie Informatik studieren und sich vorbereiten, um peinliche Wissenslücken zu vermeiden? Dann ist dieses Buch genau das richtige für Sie! Es verschafft Ihnen einen verständlichen und strukturierten Einblick in die Grundlagen der Informatik. Von der notwendigen Mathematik über erste Programmierschritte mit Python und Java bis zu Kryptografie, Datenbanken und Theoretischer Informatik ist alles dabei. Der Autor kennt die typischen Probleme und Verständnishürden der Erstsemester und hilft Ihnen, einen guten Start ins Informatikstudium zu finden. Und dazu brauchen Sie außer Schulmathe und Interesse für Informatik keinerlei Vorkenntnisse. Also los geht?s, starten Sie gut vorbereitet ins Studium. Hans Werner Lang studierte Informatik an der Universität Kiel und promovierte dort 1990 zu einem Thema aus dem Bereich "Parallele Architekturen und Algorithmen". Von 1994 bis 2017 war er Professor für Informatik an der Hochschule Flensburg und hat in dieser Zeit zahlreiche Vorlesungen zur Informatik gehalten.EINLEITUNG 19Über dieses Buch 19Konventionen in diesem Buch 19Was Sie nicht lesen müssen 20Törichte Annahmen über den Leser 20Wie dieses Buch aufgebaut ist 21Teil I: Programmieren 21Teil II: Algorithmen 21Teil III: Mathematik 21Teil IV: Codierung 22Teil V: Praktische Informatik 22Teil VI: Theoretische Informatik 22Teil VII: Top-Ten-Teil 23Symbole, die in diesem Buch verwendet werden 23Wie es weitergeht 24Bitte und Danke sagen 24TEIL I: PROGRAMMIEREN 25KAPITEL 1 PROGRAMMIEREN IN JAVA27Wertzuweisung 27Variablen deklarieren 28Wozu Datentypen? 28Einen Wert zuweisen 29Einen Wert überschreiben 30Numerische Datentypen und Operationen 31Typumwandlung bei numerischen Datentypen 32Bedingte Anweisung 33If-Anweisung 33If-Else-Anweisung 34Flussdiagramme zeichnen 35Datentyp boolean 36Boolesche Operationen 38Kommentare 39Zum Üben 39KAPITEL 2 PROGRAMMSCHLEIFEN, DATENFOLGEN UND ZEICHENKETTEN41While-Schleife 41Fakultäten berechnen 43Programmschleifen entwerfen 44Iterationsschema aufstellen 44Iterationsgleichungen ableiten 44Regeln für das Aufstellen der Iterationsgleichungen 45Iterationsgleichungen in eine While-Schleife umsetzen 45For-Schleife 46Arrays 47Array erzeugen 47Array durchlaufen 48Strings 49Strings verketten 50String-Methoden anwenden 50Zum Üben 52Iterationsschema aufstellen und in While-Schleife umsetzen 52Primzahlen mit dem Sieb des Eratosthenes 52KAPITEL 3 FUNKTIONEN55Funktionen definieren und aufrufen 55Funktionsdefinition 56Funktionsaufruf 57So funktioniert ein Stack 58Lokale Variablen benutzen 59Funktionen mit mehreren Parametern 60Funktionen ohne Parameter 61Funktionen ohne Rückgabewert 61Rekursive Funktionen 63Ausführung einer rekursiven Funktion 63Zum Üben 66Ziehung der Lottozahlen 66KAPITEL 4 OBJEKTORIENTIERT PROGRAMMIEREN69Klasse und Objekt 69Attribute und Methoden 69Kommentare und Benennungen 70Bruchrechnung 70Methoden 71Rechenoperationen mit Brüchen 73Bruch normalisieren 74Bruch kürzen 75Objektorientierung in Java 76Zum Üben 76TEIL II: ALGORITHMEN 77KAPITEL 5 ALGORITHMUS79Typische Anweisungsformen 79Algorithmisch denken 80KAPITEL 6 BINÄRE SUCHE81Suchstrategie 81Logarithmus 82Algorithmus binäre Suche 83Zum Üben 84KAPITEL 7 EINFACHES SORTIEREN85Minimum einer Datenfolge bestimmen 85Selectionsort 86Array sortieren 87Programm 87Zeitkomplexität 88Analyse von Selectionsort 89KAPITEL 8 ZEITKOMPLEXITÄT VON ALGORITHMEN91Zeitkomplexität 92Untere und obere Schranken 92Schlechtester Fall 93Asymptotische Analyse 93O-Notation 94Zum Üben 95KAPITEL 9 MERGESORT97Divide-and-Conquer-Strategie 97Ablauf von Mergesort 98Verschmelzen zweier sortierter Hälften eines Arrays 98Implementierung 99Zeitkomplexität 101Untere Schranke für das Sortieren 101Zum Üben 102KAPITEL 10 KÜRZESTE WEGE IN EINEM GRAPHEN103Idee des Verfahrens 103Greedy-Strategie 105Umsetzung in einen Algorithmus 105KAPITEL 11 KÜRZESTE RUNDREISE 107Problem des Handlungsreisenden 108Die Mengen P und NP 108Nichtdeterministischer Algorithmus 109Polynomielle Zeitkomplexität 110NP-vollständige Probleme 111Erfüllbarkeitsproblem (SAT) 112Reduktion von SAT auf CLIQUE 112TEIL III: MATHEMATIK 115KAPITEL 12 LOGIK117Logische Aussagen 117Logische Verknüpfungen 118Formale Logik 120Allgemeingültige Aussagen 121Gesetze der Logik 121Logik im Alltag 123Entweder Oder oder Entweder-Oder 123Wenn-dann in der Umgangssprache 123Die Tücken der logischen Folgerung 124Prädikate 125Quantoren 125Zum Üben 127KAPITEL 13 MENGE129Mengen bilden 129Teilmenge 131Die leere Menge 132Potenzmenge 134Mengen verknüpfen 134Komplement 135Gesetze der Mengenlehre 136Duale Gesetze 136Zum Üben 137KAPITEL 14 RELATION139Kartesisches Produkt 139Relation als Teilmenge eines kartesischen Produkts 140Schreibweise von Relationen 141Relationen anschaulich darstellen 141Eigenschaften von Relationen 143Beispiele dieser Eigenschaften 143Ordnungsrelation und Äquivalenzrelation 144Operationen auf Relationen 145n-stellige Relationen 146Wozu brauchen wir das? 146Zum Üben 147KAPITEL 15 ABBILDUNG149Abbildung als spezielle Relation 149Schreibweise für Abbildungen 151Wertetabelle einer Abbildung 151Funktion 152Verknüpfungen 153Wertetabelle einer Verknüpfung 153Verknüpfungstafel 154Eigenschaften von Abbildungen 154Injektive Abbildung 154Surjektive Abbildung 155Wertetabellen von injektiven und surjektiven Abbildungen 156Bijektive Abbildung 157Mächtigkeit von Mengen 157Folgen 158Endliche Folgen 158Zum Üben 159KAPITEL 16 GRAPH161Knoten und Kanten 161Pfad 162Baum 163Ungerichteter Graph 164Markierte Graphen 165Zum Üben 166KAPITEL 17 TEILBARKEIT UND MODULO-RECHNUNG167Teilbarkeit 167Ist null durch null teilbar? 168Teiler einer Zahl 169Größter gemeinsamer Teiler 169Primzahlen 170Modulo-Rechnung 171Modulo n rechnen 173Zum Üben 174KAPITEL 18 GRUPPEN, RINGE UND KÖRPER175Die Gruppenaxiome 175Elemente verknüpfen 176Halbgruppe 177Gruppe 178Die Gruppe 𝕫∗n179Ring 180Körper 181Zum Üben 181KAPITEL 19 BEWEISTECHNIKEN183Direkter Beweis 183Äquivalente Umformung 183Direkte Umformung 184Kontraposition 184Beweis durch Widerspruch 185Es gibt unendlich viele Primzahlen 185Varianten des Widerspruchsbeweises 186√2 ist irrational 186Gaußsche Summenformel 187Beweis durch Induktion 187Dominoeffekt 188Zum Üben 190TEIL IV: CODIERUNG 191KAPITEL 20 BOOLESCHE FUNKTIONEN193Boolesche Funktionen darstellen 194Boolesche Funktionen minimieren 195Algebraische Umformung 195KV-Diagramm 196Blöcke mit Einsen zusammenfassen 197Drei und vier Argumentvariablen 197Anwendung 199Realisierung mit Nand-Verknüpfungen 200Zum Üben 201KAPITEL 21 ZAHLENDARSTELLUNG 203Zahlensysteme zur Basis b 203Zwischen Zahl und Darstellung hin und her rechnen 204Programme 206Zahlensysteme zu anderer Basis 207Ganze Zahlen im Binärsystem 207Betrag-Vorzeichen-Darstellung 208Exzess-Darstellung 208Einerkomplement-Darstellung 209Zweierkomplement-Darstellung 209Kommazahlen im Binärsystem 210Rechnen mit Kommazahlen 211Genauigkeit von Gleitkommazahlen 211Zum Üben 212KAPITEL 22 EINFACHE CODES213Blockcodes 214Hamming-Abstand 216Fehlererkennung 216Binärcode mit Paritätsbit 217KAPITEL 23 DATEN KOMPRIMIEREN219Konstruktion des Huffman-Baums 219Konstruktion des Huffman-Codes 221Eigenschaften des Huffman-Codes 221Informationsgehalt eines Textes 222Zum Üben 222KAPITEL 24 FEHLER ERKENNEN MIT CRC223Idee des Verfahrens 223Polynom 224Polynomdivision 225Der CRC-Algorithmus 225Erkennung von Fehlern 226Zum Üben 227TEIL V: PRAKTISCHE INFORMATIK 229KAPITEL 25 DATENBANKEN231Datenbankrelationen 232Attribut 233Schlüssel 234Datenbankentwurf 235Entitäten und Beziehungen 235Schlüssel und Fremdschlüssel 236Entity-Relationship-Diagramm 237Datenbankanfragen 238Index 240Datenbankmanagementsystem 242Zum Üben 242KAPITEL 26 COMPUTERNETZE243Adressen 243Protokoll 244Protokolle im täglichen Leben 244Protokollstapel 245Schnittstellen 246Protokolle in der Informatik 246KAPITEL 27 VERSCHLÜSSELN MIT ÖFFENTLICHEM SCHLÜSSEL 249Diffie-Hellman-Schlüsselvereinbarung 250Ablauf des Verfahrens 251Problem des diskreten Logarithmus 251Public-Key-Verschlüsselung 252RSA-Verfahren 253Schlüssel erzeugen 254Sicherheit 254Berechnungsverfahren 254Primzahltest 254Schnelle Exponentiation 255Größter gemeinsamer Teiler 257Zum Üben 257TEIL VI: THEORETISCHE INFORMATIK 259KAPITEL 28 BERECHENBARKEIT261Das Halteproblem 262Praktisch nicht berechenbar 263KAPITEL 29 REGULÄRE SPRACHEN265Regulärer Ausdruck 266Reguläre Operationen 266Endlicher Automat 268Arbeitsweise des Automaten 269Formale Definition 270Deterministisch und nichtdeterministisch 271Simulation eines nichtdeterministischen endlichen Automaten 273Teilmengenkonstruktion 275Endliche Automaten und reguläre Sprachen 276Sprachen, die nicht regulär sind 277Zum Üben 278KAPITEL 30 KONTEXTFREIE GRAMMATIK UND STACKAUTOMAT279Kontextfreie Grammatik 279Wörter ableiten 280Eine Sprache erzeugen 281Wörter reduzieren 281Rechtslineare Grammatik 282Noch ein Beispiel 283Stackautomat 283Erkennung von Wörtern 285Zum Üben 286KAPITEL 31 SPRACHKLASSEN UND TURINGMASCHINEN289Hierarchie der Sprachklassen 289Die Sprachklassen L0 und L1 290Grammatiken für L0 290Grammatiken für L1 290Turingmaschine 292Formale Definition 293Arbeitsweise der Turingmaschine 293Turingtabelle 294Mit Turingmaschinen erkennbare Sprachen 295Entscheidbare Sprachen 295Nichtdeterministische und deterministischeTuringmaschinen 296KAPITEL 32 PARSER UND COMPILER299Grammatik als Ausgangspunkt 299Parser für arithmetische Ausdrücke 300Compiler für arithmetische Ausdrücke 303Basisfunktionen für Parser und Compiler 304Zum Üben 307TEIL VII: TOP-10-TEIL 309KAPITEL 33 VIER MAL SIEBEN311Die 7 elementarsten Begriffe 311Die 7 verrücktesten Dinge 312Die 7 cleversten Algorithmen 313Die 7 bedeutendsten Informatik-Pioniere 315TEIL VIII: ANHANG 317ANHANG A: LÖSUNGEN ZU DEN ÜBUNGSAUFGABEN319Teil I: Programmieren 319Teil II: Algorithmen 323Teil III: Mathematik 325Teil IV: Codierung 329Teil V: Praktische Informatik 331Teil VI: Theoretische Informatik 333ANHANG B: ZUM WEITERLESEN337Literaturverzeichnis 341Stichwortverzeichnis 345
Artificial Neural Networks with TensorFlow 2
Develop machine learning models across various domains. This book offers a single source that provides comprehensive coverage of the capabilities of TensorFlow 2 through the use of realistic, scenario-based projects.After learning what's new in TensorFlow 2, you'll dive right into developing machine learning models through applicable projects. This book covers a wide variety of ANN architectures—starting from working with a simple sequential network to advanced CNN, RNN, LSTM, DCGAN, and so on. A full chapter is devoted to each kind of network and each chapter consists of a full project describing the network architecture used, the theory behind that architecture, what data set is used, the pre-processing of data, model training, testing and performance optimizations, and analysis.This practical approach can either be used from the beginning through to the end or, if you're already familiar with basic ML models, you can dive right into the application that interests you. Line-by-line explanations on major code segments help to fill in the details as you work and the entire project source is available to you online for learning and further experimentation. With Artificial Neural Networks with TensorFlow 2 you'll see just how wide the range of TensorFlow's capabilities are.WHAT YOU'LL LEARN* Develop Machine Learning Applications* Translate languages using neural networks* Compose images with style transferWHO THIS BOOK IS FORBeginners, practitioners, and hard-cored developers who want to master machine and deep learning with TensorFlow 2. The reader should have working concepts of ML basics and terminologies.POORNACHANDRA SARANG has 30+ years of IT experience and is an experienced author. His work has always focused on state-of-the-art and emerging technologies. He has provided consulting services to—Sun Microsystems, Microsoft, Oracle, and Hewlett-Packard. He has been a Ph.D. advisor for Computer Science and is currently on a Thesis Advisory Committee for students pursuing Ph.D. in Computer Engineering—setting the course curriculum for both under-graduate and post-graduate courses in Computer Science/Engineering. He has delivered seminars, written articles, and provided consulting recently on Machine Learning and Deep Learning. He maintains a machine learning blog at education.abcom.com. Chapter 1: TensorFlowIntroductionWhat's new in TensorFlow 2Chapter 2: A Quick Start on TensorFlowHello World for TensorFlow using Google ColabChapter 3: TensorFlow Keras Integrationtf.kerasImage ClassificationChapter 4: TensorFlow HubTransfer LearningTensorFlow Hub and KerasChapter 5: RegressionPredicting Continuous Value OutputChapter 6: EstimatorsSolving Classification Problems Using EstimatorsChapter 7: Distributed TrainingDescribing tf.distribute.StrategyChapter 8: TextText ClassificationGeneration with RNNChapter 9: Language TranslationThe seq2seq model for language translationChapter 10: Language UnderstandingUsing Transformer ModelChapter 11: Image CaptioningAttention-based model for captioning imagesChapter 12: Time Series ForecastingUsing RNNsForecasting a univariate/multivariate time seriesChapter 13: Style TransferComposing an image in the style of another imageChapter 14: Image Generation using GANIntroduction to GANGenerating images using a DCGANChapter 15: Image TranslationColorizing B&W images
Red Hat and IT Security
Use Red Hat’s security tools to establish a set of security strategies that work together to help protect your digital data. You will begin with the basic concepts of IT security and DevOps with topics such as CIA triage, security standards, network and system security controls and configuration, hybrid cloud infrastructure security, and the CI/CD process. Next, you will integrate and automate security into the DevOps cycle, infrastructure, and security as code. You will also learn how to automate with Red Hat Ansible Automation Platform and about hybrid cloud infrastructure.The later chapters will cover hyper-converged infrastructure and its security, Red Hat Smart Management, predictive analytics with Red Hat Insights, and Red Hat security auditing to ensure best security practices. Lastly, you will see the different types of case studies with real-world examples.Red Hat and IT Security will help you get a better understanding of IT security concepts from a network and system administration perspective. It will help you to understand how the IT infrastructure landscape can change by implementing specific security best practices and integrating Red Hat products and solutions to counter against modern cybersecurity threats.WHAT YOU WILL LEARN● Understand IT infrastructure security and its best practices● Implement hybrid cloud infrastructure● Realign DevOps process into DevSecOps, emphasizing security● Implement automation in IT infrastructure services using Red Hat Ansible● Explore Red Hat Smart Management, predictive analytics, and auditingWHO THIS BOOK IS FORIT professionals handling network/system administration or the IT infrastructure of an organization. DevOps professionals and cybersecurity analysts would find the book useful.Rithik Chatterjee graduated as an electronics and telecommunications engineer. As he was interested in the networking domain, he completed his course in IT infrastructure management. Later on, he was accredited as a Red Hat Certified System Administrator and Red Hat Certified Engineer. Working for a startup, his responsibilities included network/system administration, IT security, information security, and DevOps. Having gained a better understanding of the IT landscape, his interest and goals leaned towards cybersecurity leading to his training and certification as an EC-Council Certified Ethical Hacker.His hobbies include landscape and wildlife photography, blogging, reading, and watching anime. To pursue his hobby of writing he developed his own blogging website (Inspirio Scripts), also encouraging budding authors like him to pen their thoughts.CHAPTER 1: INTRODUCTION TO IT SECURITYChapter Goal: Introduction to IT Security conceptsSub-Topics:Networking basicsSystem administration and IT InfrastructureStandardizing security in Red Hat Enterprise LinuxConclusionCHAPTER 2: RED HAT HYBRID CLOUD INFRASTRUCTUREChapter Goal: To understand the concepts and technologies related to cloud infrastructure and automating the security process.Sub - Topics:Basics of Cloud InfrastructureIntroduction to Hybrid Cloud ArchitectureOrchestration with Red Hat OpenShiftBuilding Hybrid Cloud with Red Hat Cloud SuiteCHAPTER 3: SECURITY IN DEVOPS AND AUTOMATIONChapter Goal: To grasp and gain a better understanding of the importance of security in DevOps and automation using Red Hat technologiesSub - Topics:Difference between DevOps and DevSecOpsAutomation with Red Hat Ansible Automation PlatformDevSecOps Integration with Red Hat OpenShiftInfrastructure as Code and Security as CodeBenefits of Red Hat ConsultingCHAPTER 4: RED HAT HYPERCONVERGED INFRASTRUCTUREChapter Goal: To learn about the advantages of using a hyper-converged infrastructure and how to ensure its security.Sub - Topics:What is a hyper-converged infrastructure?Red Hat Hyperconverged Infrastructure for VirtualizationOpen & Scalable Red Hat VirtualizationFlexibility with Red Hat Gluster StorageRed Hat Hyperconverged Infrastructure for CloudCloud Computing with Red Hat OpenStack PlatformScalability with Red Hat Ceph StorageHyperconverged Infrastructure Security best practicesCHAPTER 5: RED HAT SMART MANAGEMENT AND RED HAT INSIGHTSChapter Goal: To learn how to manage Red Hat Infrastructure across every environment and also learn about predictive analytics and how it improves the security of any infrastructureSub - Topics:Introduction to Red Hat SatelliteInfrastructure Controlling with Red Hat Smart ManagementLearn how to evaluate vulnerabilities and verify compliancePredictive analytics using Red Hat InsightsCHAPTER 6: RED HAT SECURITY AUDITINGChapter Goal: Learn about the importance and best practices of Security Auditing in Red Hat Enterprise LinuxSub - Topics:System AuditingRed Hat security auditing best practicesConclusionCHAPTER 7: CASE STUDIESChapter Goal: Learn about some of the real-world examples regarding IT Security and ramifications caused due to security negligence.Sub - Topics:Learn more about the real-world case studies related to some of the impacting IT and cybersecurity incidents and what the technological world has learned from them.
Daten- und Informationsqualität
Dieses Buch war das erste deutsche Buch zum Thema Daten- und Informationsqualität und ist mittlerweile ein Klassiker. Es wurde für die fünfte Auflage um neue Inhalte erweitert, aktualisiert und an zahlreichen Stellen überarbeitet. Von Wissenschaftlern und Praktikern geschrieben, präsentiert es den aktuellen Stand aus Forschung und Anwendung und ist somit ein Muss für alle IT-Profis.PROF. DR. KNUT HILDEBRAND ist als Hochschullehrer an der Hochschule Weihenstephan-Triesdorf mit dem Forschungsschwerpunkt Stammdatenqualität und Stammdatenmanagement tätig. Zudem war er Mitglied der Gesellschaft für Informations- und Datenqualität e.V. (DGIQ).DR. MARCUS GEBAUEr ist als Head of Department Information Technology bei der Hannover Rück AG tätig. Zudem war er Gründungsmitglied und Vorsitzender des Vorstands der Deutschen Gesellschaft für Informations- und Datenqualität e.V. (DGIQ).PROF. MICHAEL MIELKE ist Leiter Digitalisierung & Innovation DB AG, DB Training HD.l4, Leiter Campus 4.0 (www.campus40.de). Er lehrt Data Science an der FH Kiel, der HNU und der FOM und ist als Autor für die DIN ISO 8000 tätig, Zudem war er Gründungsmitglied und Präsident der Deutschen Gesellschaft für Informations- und Datenqualität e.V.Informationsqualität - Grundlagen - Methoden - Techniken - Management - Tools - Organisation - Data Governance - Praxisbeispiele
Getting Started with Containers in Google Cloud Platform
Deploy, manage, and secure containers and containerized applications on Google Cloud Platform (GCP). This book covers each container service in GCP from the ground up and teaches you how to deploy and manage your containers on each service.You will start by setting up and configuring GCP tools and the tenant environment. You then will store and manage Docker container images with GCP Container Registry (ACR). Next, you will deploy containerized applications with GCP Cloud Run and create an automated CI/CD deployment pipeline using Cloud Build. The book covers GCP’s flagship service, Google Kubernetes Service (GKE), and deployment of a Kubernetes cluster using clear steps and considering GCP best practices using the GCP management console and gcloud command-line tool. Also covered is monitoring containers and containerized applications on GCP with Cloud Monitoring, and backup and restore containers and containerized applications on GCP.By the end of the book, you will know how to get started with GCP container services and understand the fundamentals of each service and the supporting services needed to run containers in a production environment. This book also assists you in transferring your skills from AWS and Azure to GCP using the knowledge you have acquired on each platform and leveraging it to gain more skills.WHAT YOU WILL LEARN* Get started with Google Cloud Platform (GCP)* Store Docker images on GCP Container Registry * Deploy Google Kubernetes Engine (GKE) cluster* Secure containerized applications on GCP* Use Cloud Build to deploy containers * Use GCP Batch for batch job processing on KubernetesWHO THIS BOOK IS FORGoogle Cloud administrators, developers, and architects who want to get started and learn more about containers and containerized applications on Google Cloud Platform (GPC)SHIMON IFRAH is an IT professional with 15+ years of experience in the design, management, and deployment of information technology systems and networks. In recent years, he has been specializing in cloud computing and containerized applications on Microsoft Azure, Amazon AWS, and Google Cloud Platform (GCP). He holds more than 20 vendor certificates from Microsoft, AWS, VMware, and Cisco. During his career in the IT industry, he has worked for some of the largest managed services and technology companies in the world, helping them administer systems for the largest enterprises. He is based out of Melbourne, Australia. Chapter 1: Get Started with Google Cloud Platform (GCP)Chapter Goal: Setup and configure GCP tools and tenant environmentNo of pages: 40Sub -Topics1. Set up your Google Cloud Platform (GCP) tenant2. Understanding GCP projects3. Understanding cloud shell4. Secure and manage your GCP account (projects and more)5. GCP Services overviewChapter 2: Store and Manage Docker Container Images with GCP Container Registry (ACR)Chapter Goal: Here we learn how to Store Docker Container images on GCP Container registryNo of pages: 40Sub - Topics1. Setup GCP Container Registry2. Push Docker images to Container Registry3. Pull images from GCP Container Registry4. Manage and secure GCP Container RegistryChapter 3: Deploy Containerized Applications with GCP Cloud RunChapter Goal: This chapter explains how to deploy containers and containerized applications on GCP cloud runNo of pages: 40Sub - Topics:1. Set up GCP cloud run 2. Deploy containers with cloud run3. Use cloud build and git to deploy containers4. Scale containerized applications on cloud run5. Monitor and manage containerized applications on cloud runChapter 4: Deploy Containerized Applications with Google Kubernetes Engine (GKE)Chapter Goal: This chapters explains how to deploy containers and containerized applications with GKENo of pages:Sub - Topics:1. Getting started with GKE2. Setup and configure GKE networking and storage3. Deploy Kubernetes dashboard (Web UI) on GKE4. Manage and secure GKE5. Run Batch jobs on Kubernetes with batch (beta)Chapter 5: Deploy Docker Containers on GCP Compute EngineChapter Goal: This chapter explains how to deploy containers and containerized applications on GCP compute engineNo of pages: 40Sub - Topics:1. Install Docker container host on Ubuntu Linux VM2. Install Docker container host on Windows server 2019 VM3. Deploy containers on GCP compute engine using GCP container-optimized OSChapter 6: Secure your GCP Environment and ContainersChapter Goal: This chanpters explains how to secure and protect containers and containerized applications on GCPNo of pages: 40Sub - Topics:1. Introduction to GCP identify infrastructure2. Setup organization policies3. Roles, service accounts and auditing capabilities4. GCP networking and firewalls configurationChapter 7: Scale Containers and Containerized Applications on GCPChapter Goal: This chapter explains how to scale containers and containerized applications on GCPNo of pages: 40Sub - Topics:1. Scale Google Kubernetes Service (GKE)2. Scale cloud run and cloud build containers3. Scale GCP Container Registry4. Scale compute engine hosts and containersChapter 8: Monitor Containers and Containerized Applications on GCP with Stackdriver MonitoringChapter Goal: Learn how to Monitor Containers and Containerized Applications on GCPNo of pages: 40Sub - Topics:1. Monitor Google Kubernetes Service (GKE)2. Monitor cloud run containers3. Monitor compute engine resources4. GCP cost management and toolsChapter 9: Backup and Restore Containers and Containerized Applications on GCPChapter Goal: This chapter explains how to backup and restore containers and containerized applications on GCPNo of pages: 40Sub - Topics:1. Backup persistent storage disks2. Backup compute engine resources3. Manage cloud storage and file storeChapter 10: Troubleshooting Containers and Containerized Applications on GCPChapter Goal: This chapters explains how to troubleshoot containers and containerized applications issues on GCPNo of pages: 40Sub - Topics:1. Troubleshoot Google Kubernetes Service (GKE)2. Troubleshoot cloud run and cloud build deployments3. Troubleshoot GCP Container Registry5. Troubleshoot compute engine resource