Gitforgits okt 2024 (12 risultati)

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -'Statistics with Rust, Second Edition' is designed to help you learn quickly, focusing on practical statistics using Rust scripts. The book is for readers who know the basics of statistics and machine learning. It gives quick explanations so you can try out concepts with hands-on coding. The book uses the newest version of Rust, 1.72.0, to help users build and secure statistical and machine learning algorithms. Each chapter is full of useful programs and code examples that will walk you through tasks like data manipulation, statistical tests, regression analysis, building machine learning models, and natural language processing.We've covered great Rust crates featured throughout, including:ndarray and ndarray-linalg: For efficient handling of multi-dimensional arrays and linear algebra operations.ndarray-stats: To perform statistical computations on arrays.rand and rand_distr: For generating random numbers and working with probability distributions.smartcore: A machine learning library used for implementing algorithms like decision trees and random forests.linfa: A toolkit providing implementations of Support Vector Machines and other algorithms.tch: Rust bindings for PyTorch, enabling the creation and training of neural networks.finalfusion: For working with word embeddings in natural language processing tasks.rust-stemmers: To perform stemming in text preprocessing.regex: For pattern matching and text manipulation.unicode-segmentation: To accurately tokenize Unicode strings.This second edition brings all chapters up to date with the latest in stats and Rust programming. It focuses on how you can put these things to practical use, with a detailed look at advanced algorithms like PCA, SVM, neural networks, and ensemble methods. We've also included some natural language processing topics, such as text preprocessing, tokenization, and word embeddings. The book also shows you how to combine Rust's performance and safety with statistical analysis, giving you the tools you need to do data analysis efficiently and reliably. The book's got lots of practical code and explanations that are easy to understand, which helps you learn the skills you need to get to grips with data using Rust.Table of ContentIntroduction to Rust for StatisticiansData Handling and PreprocessingDescriptive StatisticsProbability Distributions and Random VariablesInferential StatisticsRegression AnalysisBayesian StatisticsMultivariate Statistical MethodsNonlinear Models and Machine LearningModel Evaluation and ValidationText and Natural Language Processing 214 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is the practical, solution-oriented book for every data scientists, machine learning engineers, and AI engineers to utilize the most of Google JAX for efficient and advanced machine learning. It covers essential tasks, troubleshooting scenarios, and optimization techniques to address common challenges encountered while working with JAX across machine learning and numerical computing projects.The book starts with the move from NumPy to JAX. It introduces the best ways to speed up computations, handle data types, generate random numbers, and perform in-place operations. It then shows you how to use profiling techniques to monitor computation time and device memory, helping you to optimize training and performance. The debugging section provides clear and effective strategies for resolving common runtime issues, including shape mismatches, NaNs, and control flow errors. The book goes on to show you how to master Pytrees for data manipulation, integrate external functions through the Foreign Function Interface (FFI), and utilize advanced serialization and type promotion techniques for stable computations.If you want to optimize training processes, this book has you covered. It includes recipes for efficient data loading, building custom neural networks, implementing mixed precision, and tracking experiments with Penzai. You'll learn how to visualize model performance and monitor metrics to assess training progress effectively. The recipes in this book tackle real-world scenarios and give users the power to fix issues and fine-tune models quickly.Key LearningsGet your calculations done faster by moving from NumPy to JAX's optimized framework.Make your training pipelines more efficient by profiling how long things take and how much memory they use.Use debugging techniques to fix runtime issues like shape mismatches and numerical instability.Get to grips with Pytrees for managing complex, nested data structures across various machine learning tasks.Use JAX's Foreign Function Interface (FFI) to bring in external functions and give your computational capabilities a boost.Take advantage of mixed-precision training to speed up neural network computations without sacrificing model accuracy.Keep your experiments on track with Penzai. This lets you reproduce results and monitor key metrics.Create your own neural networks and optimizers directly in JAX so you have full control of the architecture.Use serialization techniques to save, load, and transfer models and training checkpoints efficiently.Table of ContentTransition NumPy to JAXProfiling Computation and Device MemoryDebugging Runtime Values and ErrorsMastering Pytrees for Data StructuresExporting and SerializationType Promotion Semantics and Mixed PrecisionIntegrating Foreign Functions (FFI)Training Neural Networks with JAX Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -PostgreSQL 17 QuickStart Pro is the definitive hands-on, practical book for professionals at every level, from entry-level administrators to seasoned experts. It provides rapid learning and practical implementation of PostgreSQL 17, focusing on the latest features and best practices to effectively manage, configure, and optimize PostgreSQL databases-and it does so effectively.The book begins by using the Titanic dataset to illustrate practical examples of upgrade strategies, post-upgrade validation, and database configuration. Next, it covers cluster administration, configuration settings, and performance tracking. You will master the management of permissions and roles through intricate role hierarchies, authentication methods, and security settings. Next, we'll optimize server performance, plan queries, and manage resources based on real performance data.The next section dives deep into complicated data types, bulk data operations, advanced indexing methods, and the creation of triggers and functions, all with an emphasis on effective data management. Next, you will learn about table partitioning strategies, performing physical and logical backups, database restoration, and process automation using BART. We then move on to streaming replication, where we will configure, administer, and monitor replication to ensure optimal uptime. Finally, we will explore point-in-time recovery (PITR), which allows us to restore databases to specific points in time by replaying WAL logs. In short, this book will equip database administrators with the knowledge and skills to confidently handle PostgreSQL 17 databases.Key LearningsUpgrade and configure PostgreSQL 17, including post-upgrade validation and configuration.Learn PostgreSQL architecture, memory models, and cluster management.Use hierarchical permissions, authentication, and security for advanced role management.Tune server performance with query planning, resource management, and configuration tuning.Effectively use PostgreSQL extensions, JSONB, and arrays.Optimize queries with GIN, GiST, and BRIN indexing.Master table partitioning for large dataset performance and scalability.Automate physical and logical backups and confidently restore databases.Manage PostgreSQL streaming replication for high availability and automatic failover.Restore data using WAL logs and Point-in-Time Recovery.Table of ContentUpgrading and Setting up PostgreSQL 17Expert Database Cluster AdministrationAdvanced Database and Role ManagementConfiguration and Performance TuningEffective Data ManagementTable Partitioning StrategiesBackup and Recovery Best PracticesStreaming Replication and High AvailabilityPoint-in-Time Recovery 184 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This is the second edition of the Terraform for Developers book, presenting a thoroughly practical approach to using IaC for robust deployment and maintenance. This latest release is the most updated edition on Terraform, with the latest capabilities, patterns, and hands-on applications. Each chapter breaks down complex ideas into easy-to-follow steps, showing how to deal with the real challenges that come up in modern cloud deployments.You'll start by learning the basics, like providers, variables, and states. It also highlights some really cool modules, showing how to create, reuse, and share them across projects. Later on, it covers secrets management, showing how to store and handle sensitive data safely. It also covers advanced networking and multi-cloud usage, hurdles in bridging subnets, load balancers, and container orchestration frameworks. It also covers troubleshooting across the syntax, logic, and runtime issues that might occur. And it shows how to incorporate testing, from unit checks on modules to integration scenarios for multi-service environments.The final chapters cover advanced topics such as customizing workflows with CI/CD pipelines and using test environments. This book won't turn you into a Terraform master overnight, but it will show you all the practical features, patterns, and tricks to improve your infrastructure management.Key LearningsDiscover how Terraform streamlines resource provisioning.Write maintainable modules with confidence.Integrate advanced network constructs, subnets, and routing logic across multi-cloud topologies.Employ ephemeral credentials with Vault dynamic secrets.Automate robust tests, from unit checks to full environment validations.Practical debugging steps for syntax, semantic, and runtime errors.Adopt CI/CD pipelines to unify code reviews and automated deployments.Combine container orchestration solutions with Terraform's consistent state tracking to scale clusters.Structure microservices, security, and multi-environment usage.Track resource utilization, concurrency, and code maintainability across your stack.Table of ContentIntroduction to Terraform and IaCGetting Started with TerraformEssentials of Terraform Configuration LanguageTerraform Modules and Reusable InfrastructureTerraform State ManagementProvisioners and Provisioning ResourcesWorking with SecretsAdministering Networks with TerraformAdvanced Topics in TerraformAdministering Terraform As Expert 170 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 192 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Get certified in Node.js application development and take your career to the next level! The JSNAD certification is your ticket to proving your deep understanding and proficiency in Node.js application development. This fantastic book is perfect for anyone aiming to ace the JSNAD exam.The book is packed with essential Node.js concepts, including asynchronous programming, middleware integration, and advanced routing techniques. You'll learn about testing strategies, deployment methodologies, and performance optimization. This book includes quick reference guides and a glossary of advanced terms, making it easy to revisit key concepts and really cement your understanding. You'll also find lots of practical exercises and knowledge checks throughout the book, which are great for checking your understanding and spotting areas you can improve on. You'll find detailed explanations of complex topics that demystify intricate Node.js functionalities, making them accessible and comprehensible.And there's more! The book also offers access to sample projects and code repositories, providing hands-on experience that mirrors the scenarios encountered in the certification exam. These projects are the perfect chance for learners to put their new skills into practice, building amazing, robust Node.js applications that can scale to any challenge!Key LearningsMaster Node.js architecture and the event-driven, non-blocking I/O model.Master asynchronous programming using callbacks, promises, and async/await.Implement a robust middleware solution for efficient request handling in Express.js.Write unit tests using Mocha and Chai to ensure your code is reliable.Use Jest to test the full range of Node.js applications.Set up secure environment variables for different stages of deployment.Profile and manage your applications' memory to improve performance.Deploy your Node.js applications using PM2 and configure Nginx as a reverse proxy.Create CI/CD pipelines with GitHub Actions for automated testing and deployment.Table of ContentAdvanced Node.js ConceptsModule Systems and Package ManagementProcess Management and System InteractionNetwork Programming and SecurityFile Systems and Data StreamsAdvanced APIs and Utility ModulesPerformance Optimization and Testing 308 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -'Statistics with Rust, Second Edition' is designed to help you learn quickly, focusing on practical statistics using Rust scripts. The book is for readers who know the basics of statistics and machine learning. It gives quick explanations so you can try out concepts with hands-on coding. The book uses the newest version of Rust, 1.72.0, to help users build and secure statistical and machine learning algorithms. Each chapter is full of useful programs and code examples that will walk you through tasks like data manipulation, statistical tests, regression analysis, building machine learning models, and natural language processing.We've covered great Rust crates featured throughout, including:ndarray and ndarray-linalg: For efficient handling of multi-dimensional arrays and linear algebra operations.ndarray-stats: To perform statistical computations on arrays.rand and rand_distr: For generating random numbers and working with probability distributions.smartcore: A machine learning library used for implementing algorithms like decision trees and random forests.linfa: A toolkit providing implementations of Support Vector Machines and other algorithms.tch: Rust bindings for PyTorch, enabling the creation and training of neural networks.finalfusion: For working with word embeddings in natural language processing tasks.rust-stemmers: To perform stemming in text preprocessing.regex: For pattern matching and text manipulation.unicode-segmentation: To accurately tokenize Unicode strings.This second edition brings all chapters up to date with the latest in stats and Rust programming. It focuses on how you can put these things to practical use, with a detailed look at advanced algorithms like PCA, SVM, neural networks, and ensemble methods. We've also included some natural language processing topics, such as text preprocessing, tokenization, and word embeddings. The book also shows you how to combine Rust's performance and safety with statistical analysis, giving you the tools you need to do data analysis efficiently and reliably. The book's got lots of practical code and explanations that are easy to understand, which helps you learn the skills you need to get to grips with data using Rust.Table of ContentIntroduction to Rust for StatisticiansData Handling and PreprocessingDescriptive StatisticsProbability Distributions and Random VariablesInferential StatisticsRegression AnalysisBayesian StatisticsMultivariate Statistical MethodsNonlinear Models and Machine LearningModel Evaluation and ValidationText and Natural Language ProcessingLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 214 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This is the practical, solution-oriented book for every data scientists, machine learning engineers, and AI engineers to utilize the most of Google JAX for efficient and advanced machine learning. It covers essential tasks, troubleshooting scenarios, and optimization techniques to address common challenges encountered while working with JAX across machine learning and numerical computing projects.The book starts with the move from NumPy to JAX. It introduces the best ways to speed up computations, handle data types, generate random numbers, and perform in-place operations. It then shows you how to use profiling techniques to monitor computation time and device memory, helping you to optimize training and performance. The debugging section provides clear and effective strategies for resolving common runtime issues, including shape mismatches, NaNs, and control flow errors. The book goes on to show you how to master Pytrees for data manipulation, integrate external functions through the Foreign Function Interface (FFI), and utilize advanced serialization and type promotion techniques for stable computations.If you want to optimize training processes, this book has you covered. It includes recipes for efficient data loading, building custom neural networks, implementing mixed precision, and tracking experiments with Penzai. You'll learn how to visualize model performance and monitor metrics to assess training progress effectively. The recipes in this book tackle real-world scenarios and give users the power to fix issues and fine-tune models quickly.Key LearningsGet your calculations done faster by moving from NumPy to JAX's optimized framework.Make your training pipelines more efficient by profiling how long things take and how much memory they use.Use debugging techniques to fix runtime issues like shape mismatches and numerical instability.Get to grips with Pytrees for managing complex, nested data structures across various machine learning tasks.Use JAX's Foreign Function Interface (FFI) to bring in external functions and give your computational capabilities a boost.Take advantage of mixed-precision training to speed up neural network computations without sacrificing model accuracy.Keep your experiments on track with Penzai. This lets you reproduce results and monitor key metrics.Create your own neural networks and optimizers directly in JAX so you have full control of the architecture.Use serialization techniques to save, load, and transfer models and training checkpoints efficiently.Table of ContentTransition NumPy to JAXProfiling Computation and Device MemoryDebugging Runtime Values and ErrorsMastering Pytrees for Data StructuresExporting and SerializationType Promotion Semantics and Mixed PrecisionIntegrating Foreign Functions (FFI)Training Neural Networks with JAXLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 252 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -PostgreSQL 17 QuickStart Pro is the definitive hands-on, practical book for professionals at every level, from entry-level administrators to seasoned experts. It provides rapid learning and practical implementation of PostgreSQL 17, focusing on the latest features and best practices to effectively manage, configure, and optimize PostgreSQL databases-and it does so effectively.The book begins by using the Titanic dataset to illustrate practical examples of upgrade strategies, post-upgrade validation, and database configuration. Next, it covers cluster administration, configuration settings, and performance tracking. You will master the management of permissions and roles through intricate role hierarchies, authentication methods, and security settings. Next, we'll optimize server performance, plan queries, and manage resources based on real performance data.The next section dives deep into complicated data types, bulk data operations, advanced indexing methods, and the creation of triggers and functions, all with an emphasis on effective data management. Next, you will learn about table partitioning strategies, performing physical and logical backups, database restoration, and process automation using BART. We then move on to streaming replication, where we will configure, administer, and monitor replication to ensure optimal uptime. Finally, we will explore point-in-time recovery (PITR), which allows us to restore databases to specific points in time by replaying WAL logs. In short, this book will equip database administrators with the knowledge and skills to confidently handle PostgreSQL 17 databases.Key LearningsUpgrade and configure PostgreSQL 17, including post-upgrade validation and configuration.Learn PostgreSQL architecture, memory models, and cluster management.Use hierarchical permissions, authentication, and security for advanced role management.Tune server performance with query planning, resource management, and configuration tuning.Effectively use PostgreSQL extensions, JSONB, and arrays.Optimize queries with GIN, GiST, and BRIN indexing.Master table partitioning for large dataset performance and scalability.Automate physical and logical backups and confidently restore databases.Manage PostgreSQL streaming replication for high availability and automatic failover.Restore data using WAL logs and Point-in-Time Recovery.Table of ContentUpgrading and Setting up PostgreSQL 17Expert Database Cluster AdministrationAdvanced Database and Role ManagementConfiguration and Performance TuningEffective Data ManagementTable Partitioning StrategiesBackup and Recovery Best PracticesStreaming Replication and High AvailabilityPoint-in-Time RecoveryLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 184 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This is the second edition of the Terraform for Developers book, presenting a thoroughly practical approach to using IaC for robust deployment and maintenance. This latest release is the most updated edition on Terraform, with the latest capabilities, patterns, and hands-on applications. Each chapter breaks down complex ideas into easy-to-follow steps, showing how to deal with the real challenges that come up in modern cloud deployments.You'll start by learning the basics, like providers, variables, and states. It also highlights some really cool modules, showing how to create, reuse, and share them across projects. Later on, it covers secrets management, showing how to store and handle sensitive data safely. It also covers advanced networking and multi-cloud usage, hurdles in bridging subnets, load balancers, and container orchestration frameworks. It also covers troubleshooting across the syntax, logic, and runtime issues that might occur. And it shows how to incorporate testing, from unit checks on modules to integration scenarios for multi-service environments.The final chapters cover advanced topics such as customizing workflows with CI/CD pipelines and using test environments. This book won't turn you into a Terraform master overnight, but it will show you all the practical features, patterns, and tricks to improve your infrastructure management.Key LearningsDiscover how Terraform streamlines resource provisioning.Write maintainable modules with confidence.Integrate advanced network constructs, subnets, and routing logic across multi-cloud topologies.Employ ephemeral credentials with Vault dynamic secrets.Automate robust tests, from unit checks to full environment validations.Practical debugging steps for syntax, semantic, and runtime errors.Adopt CI/CD pipelines to unify code reviews and automated deployments.Combine container orchestration solutions with Terraform's consistent state tracking to scale clusters.Structure microservices, security, and multi-environment usage.Track resource utilization, concurrency, and code maintainability across your stack.Table of ContentIntroduction to Terraform and IaCGetting Started with TerraformEssentials of Terraform Configuration LanguageTerraform Modules and Reusable InfrastructureTerraform State ManagementProvisioners and Provisioning ResourcesWorking with SecretsAdministering Networks with TerraformAdvanced Topics in TerraformAdministering Terraform As ExpertLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 170 pp. Englisch.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware Libri GmbH, Europaallee 1, 36244 Bad Hersfeld 192 pp. Englisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Get certified in Node.js application development and take your career to the next level! The JSNAD certification is your ticket to proving your deep understanding and proficiency in Node.js application development. This fantastic book is perfect for anyone aiming to ace the JSNAD exam.The book is packed with essential Node.js concepts, including asynchronous programming, middleware integration, and advanced routing techniques. You'll learn about testing strategies, deployment methodologies, and performance optimization. This book includes quick reference guides and a glossary of advanced terms, making it easy to revisit key concepts and really cement your understanding. You'll also find lots of practical exercises and knowledge checks throughout the book, which are great for checking your understanding and spotting areas you can improve on. You'll find detailed explanations of complex topics that demystify intricate Node.js functionalities, making them accessible and comprehensible.And there's more! The book also offers access to sample projects and code repositories, providing hands-on experience that mirrors the scenarios encountered in the certification exam. These projects are the perfect chance for learners to put their new skills into practice, building amazing, robust Node.js applications that can scale to any challenge!Key LearningsMaster Node.js architecture and the event-driven, non-blocking I/O model.Master asynchronous programming using callbacks, promises, and async/await.Implement a robust middleware solution for efficient request handling in Express.js.Write unit tests using Mocha and Chai to ensure your code is reliable.Use Jest to test the full range of Node.js applications.Set up secure environment variables for different stages of deployment.Profile and manage your applications' memory to improve performance.Deploy your Node.js applications using PM2 and configure Nginx as a reverse proxy.Create CI/CD pipelines with GitHub Actions for automated testing and deployment.Table of ContentAdvanced Node.js ConceptsModule Systems and Package ManagementProcess Management and System InteractionNetwork Programming and SecurityFile Systems and Data StreamsAdvanced APIs and Utility ModulesPerformance Optimization and TestingLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 308 pp. Englisch.…