Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd Edition
Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. ...
Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. ...
C# 11 and .NET 7 - Modern Cross-Platform Development Fundamentals, 7th Edition
Extensively revised to accommodate the latest features that come with C# 11 and .NET 7, this latest edition of our guide will get you coding in C# with confidence. You'll learn object-oriented programming, writing, testing, and debugging functions, implementing interfaces, and inheriting classes. Next, you'll take on .NET APIs for performing tasks like managing and querying data, working with the filesystem, and serialization. As you progress, you'll also explore examples of cross-platform projects you can build and deploy, such as websites and services using ASP.NET Core. Instead of distracting you with unnecessary graphical user interface code, the first eleven chapters will teach you about C# language constructs and many of the .NET libraries through simple console applications. In later chapters, having mastered the basics, you'll then build websites, web services, and browser apps using ASP.NET Core, the Model-View-Controller (MVC) pattern, and Blazor. C# 11 and .NET 7 - ...
Extensively revised to accommodate the latest features that come with C# 11 and .NET 7, this latest edition of our guide will get you coding in C# with confidence. You'll learn object-oriented programming, writing, testing, and debugging functions, implementing interfaces, and inheriting classes. Next, you'll take on .NET APIs for performing tasks like managing and querying data, working with the filesystem, and serialization. As you progress, you'll also explore examples of cross-platform projects you can build and deploy, such as websites and services using ASP.NET Core. Instead of distracting you with unnecessary graphical user interface code, the first eleven chapters will teach you about C# language constructs and many of the .NET libraries through simple console applications. In later chapters, having mastered the basics, you'll then build websites, web services, and browser apps using ASP.NET Core, the Model-View-Controller (MVC) pattern, and Blazor. C# 11 and .NET 7 - ...
Learning Blazor
Take advantage of your C# skills to build UI components and client-side experiences with .NET. With this practical guide, you'll learn how to use Blazor WebAssembly to develop next-generation web experiences. Built on top of ASP.NET Core, Blazor represents the future of .NET single-page applications (SPA) investments. Author David Pine, who focuses on .NET and Azure content development at Microsoft, explains how WebAssembly enables many non-JavaScript-based programming languages to run on the client browser. In this book, you'll learn about real-time web functionality with ASP.NET Core SignalR. You'll learn strategies for bidirectional JavaScript interop. David covers component data binding, hierarchical event-driven communications, in-memory state management, and local storage. ...
Take advantage of your C# skills to build UI components and client-side experiences with .NET. With this practical guide, you'll learn how to use Blazor WebAssembly to develop next-generation web experiences. Built on top of ASP.NET Core, Blazor represents the future of .NET single-page applications (SPA) investments. Author David Pine, who focuses on .NET and Azure content development at Microsoft, explains how WebAssembly enables many non-JavaScript-based programming languages to run on the client browser. In this book, you'll learn about real-time web functionality with ASP.NET Core SignalR. You'll learn strategies for bidirectional JavaScript interop. David covers component data binding, hierarchical event-driven communications, in-memory state management, and local storage. ...
Architecting and Building High-Speed SoCs
Modern and complex SoCs can adapt to many demanding system requirements by combining the processing power of ARM processors and the feature-rich Xilinx FPGAs. You'll need to understand many protocols, use a variety of internal and external interfaces, pinpoint the bottlenecks, and define the architecture of an SoC in an FPGA to produce a superior solution in a timely and cost-efficient manner. This book adopts a practical approach to helping you master both the hardware and software design flows, understand key interconnects and interfaces, analyze the system performance and enhance it using the acceleration techniques, and finally build an RTOS-based software application for an advanced SoC design. You'll start with an introduction to the FPGA SoCs technology fundamentals and their associated development design tools. Gradually, the book will guide you through building the SoC hardware and software, starting from the architecture definition to testing on a demo board or a virtua ...
Modern and complex SoCs can adapt to many demanding system requirements by combining the processing power of ARM processors and the feature-rich Xilinx FPGAs. You'll need to understand many protocols, use a variety of internal and external interfaces, pinpoint the bottlenecks, and define the architecture of an SoC in an FPGA to produce a superior solution in a timely and cost-efficient manner. This book adopts a practical approach to helping you master both the hardware and software design flows, understand key interconnects and interfaces, analyze the system performance and enhance it using the acceleration techniques, and finally build an RTOS-based software application for an advanced SoC design. You'll start with an introduction to the FPGA SoCs technology fundamentals and their associated development design tools. Gradually, the book will guide you through building the SoC hardware and software, starting from the architecture definition to testing on a demo board or a virtua ...
Python Data Science Handbook, 2nd Edition
Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all - IPython, NumPy, pandas, Matplotlib, scikit-learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. ...
Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all - IPython, NumPy, pandas, Matplotlib, scikit-learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. ...
Pro DAX and Data Modeling in Power BI
Develop powerful data models that bind data from disparate sources into a coherent whole. Then extend your data models using DAX - the query language that underpins Power BI - to create reusable measures to deliver finely-crafted custom calculations in your dashboards. This book starts off teaching you how to define and enhance the core structures of your data model to make it a true semantic layer that transforms complex data into familiar business terms. You'll learn how to create calculated columns to solve basic analytical challenges. Then you'll move up to mastering DAX measures to finely slice and dice your data. The book also shows how to handle temporal analysis in Power BI using a Date dimension. You will see how DAX Time Intelligence functions can simplify your analysis of data over time. Finally, the book shows how to extend DAX to filter and calculate datasets and develop DAX table functions and variables to handle complex queries. ...
Develop powerful data models that bind data from disparate sources into a coherent whole. Then extend your data models using DAX - the query language that underpins Power BI - to create reusable measures to deliver finely-crafted custom calculations in your dashboards. This book starts off teaching you how to define and enhance the core structures of your data model to make it a true semantic layer that transforms complex data into familiar business terms. You'll learn how to create calculated columns to solve basic analytical challenges. Then you'll move up to mastering DAX measures to finely slice and dice your data. The book also shows how to handle temporal analysis in Power BI using a Date dimension. You will see how DAX Time Intelligence functions can simplify your analysis of data over time. Finally, the book shows how to extend DAX to filter and calculate datasets and develop DAX table functions and variables to handle complex queries. ...
Numerical Methods Using Kotlin
This in-depth guide covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started. In this book, you'll implement numerical algorithms in Kotlin using NM Dev, an object-oriented and high-performance programming library for applied and industrial mathematics. Discover how Kotlin has many advantages over Java in its speed, and in some cases, ease of use. In this book, you'll see how it can help you easily create solutions for your complex engineering and data science problems. After reading this book, you'll come away with the knowledge to create your own numerical models and algori ...
This in-depth guide covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started. In this book, you'll implement numerical algorithms in Kotlin using NM Dev, an object-oriented and high-performance programming library for applied and industrial mathematics. Discover how Kotlin has many advantages over Java in its speed, and in some cases, ease of use. In this book, you'll see how it can help you easily create solutions for your complex engineering and data science problems. After reading this book, you'll come away with the knowledge to create your own numerical models and algori ...
Advanced Data Analytics Using Python, 2nd Edition
Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpa ...
Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpa ...
Machine Learning with R, 4th Edition
Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Fourth Edition, provides a hands-on, accessible, and readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to know for data pre-processing, uncovering key insights, making new predictions, and visualizing your findings. This 10th Anniversary Edition features several new chapters that reflect the progress of machine learning in the last few years and help you build your data science skills and tackle more challenging problems, including making successful machine learning models and advanced data preparation, building better learners, and making use of big data. You'll also find this classic R data science book updated to R 4.0.0 with newer and better ...
Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Fourth Edition, provides a hands-on, accessible, and readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to know for data pre-processing, uncovering key insights, making new predictions, and visualizing your findings. This 10th Anniversary Edition features several new chapters that reflect the progress of machine learning in the last few years and help you build your data science skills and tackle more challenging problems, including making successful machine learning models and advanced data preparation, building better learners, and making use of big data. You'll also find this classic R data science book updated to R 4.0.0 with newer and better ...
AWS for Solutions Architects, 2nd Edition
Are you excited to harness the power of AWS and unlock endless possibilities for your business? Look no further than the second edition of AWS for Solutions Architects! Packed with all-new content, this book is a must-have guide for anyone looking to build scalable cloud solutions and drive digital transformation using AWS. This updated edition offers in-depth guidance for building cloud solutions using AWS. It provides detailed information on AWS well-architected design pillars and cloud-native design patterns. You'll learn about networking in AWS, big data and streaming data processing, CloudOps, and emerging technologies such as machine learning, IoT, and blockchain. Additionally, the book includes new sections on storage in AWS, containers with ECS and EKS, and data lake patterns, providing you with valuable insights into designing industry-standard AWS architectures that meet your organization's technological and business requirements. Whether you're an experienced solutions archi ...
Are you excited to harness the power of AWS and unlock endless possibilities for your business? Look no further than the second edition of AWS for Solutions Architects! Packed with all-new content, this book is a must-have guide for anyone looking to build scalable cloud solutions and drive digital transformation using AWS. This updated edition offers in-depth guidance for building cloud solutions using AWS. It provides detailed information on AWS well-architected design pillars and cloud-native design patterns. You'll learn about networking in AWS, big data and streaming data processing, CloudOps, and emerging technologies such as machine learning, IoT, and blockchain. Additionally, the book includes new sections on storage in AWS, containers with ECS and EKS, and data lake patterns, providing you with valuable insights into designing industry-standard AWS architectures that meet your organization's technological and business requirements. Whether you're an experienced solutions archi ...