The Go Workshop
You already know you want to learn Go, and the smart way to learn anything is to learn by doing. The Go Workshop focuses on building up your practical skills so that you can develop high-performing concurrent applications, or even create Go scripts to automate repetitive daily tasks. You'll learn from real examples that lead to real results. Throughout The Go Workshop, you'll take an engaging step-by-step approach to understanding Go. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day, or you can spend an entire weekend learning how to test and secure your Go applications. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Go Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessment ...
You already know you want to learn Go, and the smart way to learn anything is to learn by doing. The Go Workshop focuses on building up your practical skills so that you can develop high-performing concurrent applications, or even create Go scripts to automate repetitive daily tasks. You'll learn from real examples that lead to real results. Throughout The Go Workshop, you'll take an engaging step-by-step approach to understanding Go. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day, or you can spend an entire weekend learning how to test and secure your Go applications. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Go Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessment ...
Mastering Go, 2nd Edition
Often referred to (incorrectly) as Golang, Go is the high-performance systems language of the future. Mastering Go, Second Edition helps you become a productive expert Go programmer, building and improving on the groundbreaking first edition. Mastering Go, Second Edition shows how to put Go to work on real production systems. For programmers who already know the Go language basics, this book provides examples, patterns, and clear explanations to help you deeply understand Go's capabilities and apply them in your programming work. The book covers the nuances of Go, with in-depth guides on types and structures, packages, concurrency, network programming, compiler design, optimization, and more. Each chapter ends with exercises and resources to fully embed your new knowledge. This second edition includes a completely new chapter on machine learning in Go, guiding you from the foundation statistics techniques through simple regression and clustering to classification, neural netwo ...
Often referred to (incorrectly) as Golang, Go is the high-performance systems language of the future. Mastering Go, Second Edition helps you become a productive expert Go programmer, building and improving on the groundbreaking first edition. Mastering Go, Second Edition shows how to put Go to work on real production systems. For programmers who already know the Go language basics, this book provides examples, patterns, and clear explanations to help you deeply understand Go's capabilities and apply them in your programming work. The book covers the nuances of Go, with in-depth guides on types and structures, packages, concurrency, network programming, compiler design, optimization, and more. Each chapter ends with exercises and resources to fully embed your new knowledge. This second edition includes a completely new chapter on machine learning in Go, guiding you from the foundation statistics techniques through simple regression and clustering to classification, neural netwo ...
Deep Learning with TensorFlow 2 and Keras, 2nd Edition
Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. ...
Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. ...
Advanced Deep Learning with Python
In order to build robust deep learning systems, you'll need to understand everything from how neural networks work to training CNN models. In this book, you'll discover newly developed deep learning models, methodologies used in the domain, and their implementation based on areas of application. You'll start by understanding the building blocks and the math behind neural networks, and then move on to CNNs and their advanced applications in computer vision. You'll also learn to apply the most popular CNN architectures in object detection and image segmentation. Further on, you'll focus on variational autoencoders and GANs. You'll then use neural networks to extract sophisticated vector representations of words, before going on to cover various types of recurrent networks, such as LSTM and GRU. You'll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs). Later, you'll use graph neural networks for processing structured da ...
In order to build robust deep learning systems, you'll need to understand everything from how neural networks work to training CNN models. In this book, you'll discover newly developed deep learning models, methodologies used in the domain, and their implementation based on areas of application. You'll start by understanding the building blocks and the math behind neural networks, and then move on to CNNs and their advanced applications in computer vision. You'll also learn to apply the most popular CNN architectures in object detection and image segmentation. Further on, you'll focus on variational autoencoders and GANs. You'll then use neural networks to extract sophisticated vector representations of words, before going on to cover various types of recurrent networks, such as LSTM and GRU. You'll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs). Later, you'll use graph neural networks for processing structured da ...
AI Crash Course
Welcome to the Robot World ... and start building intelligent software now! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch. AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. ...
Welcome to the Robot World ... and start building intelligent software now! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of thousands of people to write AI software. Now, for the first time, his hands-on, energetic approach is available as a book. Starting with the basics before easing you into more complicated formulas and notation, AI Crash Course gives you everything you need to build AI systems with reinforcement learning and deep learning. Five full working projects put the ideas into action, showing step-by-step how to build intelligent software using the best and easiest tools for AI programming, including Python, TensorFlow, Keras, and PyTorch. AI Crash Course teaches everyone to build an AI to work in their applications. Once you've read this book, you're only limited by your imagination. ...
Python Feature Engineering Cookbook
Feature engineering is invaluable for developing and enriching your machine learning models. In this cookbook, you will work with the best tools to streamline your feature engineering pipelines and techniques and simplify and improve the quality of your code. Using Python libraries such as pandas, scikit-learn, Featuretools, and Feature-engine, you'll learn how to work with both continuous and discrete datasets and be able to transform features from unstructured datasets. You will develop the skills necessary to select the best features as well as the most suitable extraction techniques. This book will cover Python recipes that will help you automate feature engineering to simplify complex processes. You'll also get to grips with different feature engineering strategies, such as the box-cox transform, power transform, and log transform across machine learning, reinforcement learning, and natural language processing (NLP) domains. By the end of this book, you'll have discovered ti ...
Feature engineering is invaluable for developing and enriching your machine learning models. In this cookbook, you will work with the best tools to streamline your feature engineering pipelines and techniques and simplify and improve the quality of your code. Using Python libraries such as pandas, scikit-learn, Featuretools, and Feature-engine, you'll learn how to work with both continuous and discrete datasets and be able to transform features from unstructured datasets. You will develop the skills necessary to select the best features as well as the most suitable extraction techniques. This book will cover Python recipes that will help you automate feature engineering to simplify complex processes. You'll also get to grips with different feature engineering strategies, such as the box-cox transform, power transform, and log transform across machine learning, reinforcement learning, and natural language processing (NLP) domains. By the end of this book, you'll have discovered ti ...
Modern Full-Stack Development
Explore what React, Node, TypeScript, Webpack, and Docker have to offer individually, and how they all fit together in modern app development. React is one of the most popular web development tools available today, and Node.js is extremely popular for server-side development. The fact that both utilize JavaScript is a big selling point, but as developers use the language more, they begin to recognize the shortcomings, and that's where TypeScript comes in and why it's gaining in popularity quickly. Add Webpack and Docker to the mix, and you've got a potent full development stack on which to build applications. You'll begin by building a solid foundation of knowledge and quickly expand it by constructing two different real-world apps. These aren't just simple, contrived examples but real apps that you can choose to install on your servers and use for real. By the end, you will have a solid grasp of building apps with React, Node.js, and TypeScript and a good grasp on how Webpack ca ...
Explore what React, Node, TypeScript, Webpack, and Docker have to offer individually, and how they all fit together in modern app development. React is one of the most popular web development tools available today, and Node.js is extremely popular for server-side development. The fact that both utilize JavaScript is a big selling point, but as developers use the language more, they begin to recognize the shortcomings, and that's where TypeScript comes in and why it's gaining in popularity quickly. Add Webpack and Docker to the mix, and you've got a potent full development stack on which to build applications. You'll begin by building a solid foundation of knowledge and quickly expand it by constructing two different real-world apps. These aren't just simple, contrived examples but real apps that you can choose to install on your servers and use for real. By the end, you will have a solid grasp of building apps with React, Node.js, and TypeScript and a good grasp on how Webpack ca ...
React and React Native, 3rd Edition
React and React Native, Facebook's innovative User Interface (UI) libraries, are designed to help you build robust cross-platform web and mobile applications. This updated third edition is improved and updated to cover the latest version of React. The book particularly focuses on the latest developments in the React ecosystem, such as modern Hook implementations, code splitting using lazy components and Suspense, user interface framework components using Material-UI, and Apollo. In terms of React Native, the book has been updated to version 0.62 and demonstrates how to apply native UI components for your existing mobile apps using NativeBase. You will begin by learning about the essential building blocks of React components. Next, you'll progress to working with higher-level functionalities in application development, before putting this knowledge to use by developing user interface components for the web and for native platforms. In the concluding chapters, you'll learn how to brin ...
React and React Native, Facebook's innovative User Interface (UI) libraries, are designed to help you build robust cross-platform web and mobile applications. This updated third edition is improved and updated to cover the latest version of React. The book particularly focuses on the latest developments in the React ecosystem, such as modern Hook implementations, code splitting using lazy components and Suspense, user interface framework components using Material-UI, and Apollo. In terms of React Native, the book has been updated to version 0.62 and demonstrates how to apply native UI components for your existing mobile apps using NativeBase. You will begin by learning about the essential building blocks of React components. Next, you'll progress to working with higher-level functionalities in application development, before putting this knowledge to use by developing user interface components for the web and for native platforms. In the concluding chapters, you'll learn how to brin ...
Machine Learning with R, the tidyverse, and mlr
Machine learning (ML) is a collection of programming techniques for discovering relationships in data. With ML algorithms, you can cluster and classify data for tasks like making recommendations or fraud detection and make predictions for sales trends, risk analysis, and other forecasts. Once the domain of academic data scientists, machine learning has become a mainstream business process, and tools like the easy-to-learn R programming language put high-quality data analysis in the hands of any programmer. Machine Learning with R, the tidyverse, and mlr teaches you widely used ML techniques and how to apply them to your own datasets using the R programming language and its powerful ecosystem of tools. This book will get you started! Machine Learning with R, the tidyverse, and mlr gets you started in machine learning using R Studio and the awesome mlr machine learning package. This practical guide simplifies theory and avoids needlessly complicated statistics or math. All core ML tec ...
Machine learning (ML) is a collection of programming techniques for discovering relationships in data. With ML algorithms, you can cluster and classify data for tasks like making recommendations or fraud detection and make predictions for sales trends, risk analysis, and other forecasts. Once the domain of academic data scientists, machine learning has become a mainstream business process, and tools like the easy-to-learn R programming language put high-quality data analysis in the hands of any programmer. Machine Learning with R, the tidyverse, and mlr teaches you widely used ML techniques and how to apply them to your own datasets using the R programming language and its powerful ecosystem of tools. This book will get you started! Machine Learning with R, the tidyverse, and mlr gets you started in machine learning using R Studio and the awesome mlr machine learning package. This practical guide simplifies theory and avoids needlessly complicated statistics or math. All core ML tec ...
Deep Reinforcement Learning in Action
Humans learn best from feedback - we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you'll need to implement it into your own projects. Deep reinforcement learning AI systems rapidly adapt to new environments, a vast improvement over standard neural networks. A DRL agent learns like people do, taking in raw data such as sensor input and refining its responses and predictions through trial and error. Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you'll master foundational and ...
Humans learn best from feedback - we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you'll need to implement it into your own projects. Deep reinforcement learning AI systems rapidly adapt to new environments, a vast improvement over standard neural networks. A DRL agent learns like people do, taking in raw data such as sensor input and refining its responses and predictions through trial and error. Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you'll master foundational and ...