Get Programming with Node.js
Get Programming with Node.js Get Programming with Node.js teaches you to write server-side code in JavaScript using Node.js. In 37 fast-paced, fun, and practical lessons, you'll discover how to extend your existing JavaScript skills to write back-end code for your web applications. Node.js delivers the speed and reliability you need for ecommerce, social media, and gaming applications. It comes with thousands of prebuilt packages to help you get started immediately. If you want to use JavaScript on the server, Node.js is your choice. Get Programming with Node.js teaches you to build web servers using JavaScript and Node. In this engaging tutorial, you'll work through eight complete projects, from writing the code for your first web server to adding live chat to a web app. Your hands will stay on the keyboard as you explore the most important aspects of the Node development process, including security, database management, authenticating user accounts, and deploying to production. ...
Get Programming with Node.js Get Programming with Node.js teaches you to write server-side code in JavaScript using Node.js. In 37 fast-paced, fun, and practical lessons, you'll discover how to extend your existing JavaScript skills to write back-end code for your web applications. Node.js delivers the speed and reliability you need for ecommerce, social media, and gaming applications. It comes with thousands of prebuilt packages to help you get started immediately. If you want to use JavaScript on the server, Node.js is your choice. Get Programming with Node.js teaches you to build web servers using JavaScript and Node. In this engaging tutorial, you'll work through eight complete projects, from writing the code for your first web server to adding live chat to a web app. Your hands will stay on the keyboard as you explore the most important aspects of the Node development process, including security, database management, authenticating user accounts, and deploying to production. ...
Learning C++ by Building Games with Unreal Engine 4, 2nd Edition
Learning to program in C++ requires some serious motivation. Unreal Engine 4 (UE4) is a powerful C++ engine with a full range of features used to create top-notch, exciting games by AAA studios, making it the fun way to dive into learning C++17. This book starts by installing a code editor so you can begin to write C++17 code. You will then get acquainted with important C++ aspects, such as variables and memory, if, else, and switch, looping, functions and macros, objects, classes, inheritance, and dynamic memory allocation. As we dig into more advanced C++17 concepts, you will also start to explore the functionality the UE4 engine has to offer. You will use the UE4 editor to create your own world, and then program in some seriously fun gameplay. We delve further to discuss building game features, pathfinding, behavior trees, and more, and introduce you to the basics of machine learning and neural networks. We go on to talk about improving UI feedback with UMG and audio. In this edi ...
Learning to program in C++ requires some serious motivation. Unreal Engine 4 (UE4) is a powerful C++ engine with a full range of features used to create top-notch, exciting games by AAA studios, making it the fun way to dive into learning C++17. This book starts by installing a code editor so you can begin to write C++17 code. You will then get acquainted with important C++ aspects, such as variables and memory, if, else, and switch, looping, functions and macros, objects, classes, inheritance, and dynamic memory allocation. As we dig into more advanced C++17 concepts, you will also start to explore the functionality the UE4 engine has to offer. You will use the UE4 editor to create your own world, and then program in some seriously fun gameplay. We delve further to discuss building game features, pathfinding, behavior trees, and more, and introduce you to the basics of machine learning and neural networks. We go on to talk about improving UI feedback with UMG and audio. In this edi ...
PyTorch Deep Learning Hands-On
PyTorch Deep Learning Hands-On is a book for engineers who want a fast-paced guide to doing deep learning work with PyTorch. It is not an academic textbook and does not try to teach deep learning principles. The book will help you most if you want to get your hands dirty and put PyTorch to work quickly. PyTorch Deep Learning Hands-On shows how to implement the major deep learning architectures in PyTorch. It covers neural networks, computer vision, CNNs, natural language processing (RNN), GANs, and reinforcement learning. You will also build deep learning workflows with the PyTorch framework, migrate models built in Python to highly efficient TorchScript, and deploy to production using the most sophisticated available tools. Each chapter focuses on a different area of deep learning. Chapters start with a refresher on how the model works, before sharing the code you need to implement it in PyTorch. This book is ideal if you want to rapidly add PyTorch to your deep learning tool ...
PyTorch Deep Learning Hands-On is a book for engineers who want a fast-paced guide to doing deep learning work with PyTorch. It is not an academic textbook and does not try to teach deep learning principles. The book will help you most if you want to get your hands dirty and put PyTorch to work quickly. PyTorch Deep Learning Hands-On shows how to implement the major deep learning architectures in PyTorch. It covers neural networks, computer vision, CNNs, natural language processing (RNN), GANs, and reinforcement learning. You will also build deep learning workflows with the PyTorch framework, migrate models built in Python to highly efficient TorchScript, and deploy to production using the most sophisticated available tools. Each chapter focuses on a different area of deep learning. Chapters start with a refresher on how the model works, before sharing the code you need to implement it in PyTorch. This book is ideal if you want to rapidly add PyTorch to your deep learning tool ...
Deep Learning Pipeline
Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets. You'll also develop a deep learning project by preparing data, choosing the model that fits that data, and debugging your model to get the best fit to data all using Tensorflow techniques. Enhance your skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution or en ...
Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets. You'll also develop a deep learning project by preparing data, choosing the model that fits that data, and debugging your model to get the best fit to data all using Tensorflow techniques. Enhance your skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution or en ...
Advanced Deep Learning with TensorFlow 2 and Keras, 2nd Edition
Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised for TensorFlow 2.x, this edition introduces you to the practical side of deep learning with new chapters on unsupervised learning using mutual information, object detection (SSD), and semantic segmentation (FCN and PSPNet), further allowing you to create your own cutting-edge AI projects. Using Keras as an open-source deep learning library, the book features hands-on projects that show you how to create more effective AI with the most up-to-date techniques. Starting with an overview of multi-layer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), the book then introduces more cutting-edge techniques as you explore deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders. You will then learn about GANs, and ho ...
Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised for TensorFlow 2.x, this edition introduces you to the practical side of deep learning with new chapters on unsupervised learning using mutual information, object detection (SSD), and semantic segmentation (FCN and PSPNet), further allowing you to create your own cutting-edge AI projects. Using Keras as an open-source deep learning library, the book features hands-on projects that show you how to create more effective AI with the most up-to-date techniques. Starting with an overview of multi-layer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs), the book then introduces more cutting-edge techniques as you explore deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders. You will then learn about GANs, and ho ...
Python Machine Learning, 3rd Edition
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, ...
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, ...
Mastering Machine Learning Algorithms, 2nd Edition
Mastering Machine Learning Algorithms, 2nd Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and unsupervised learning domains. You will use all the modern libraries from the Python ecosystem - including NumPy and Keras - to extract features from varied complexities of data. Ranging from Bayesian models to the Markov chain Monte Carlo algorithm to Hidden Markov models, this machine learning book teaches you how to extract features from your dataset, perform complex dimensionality reduction, and train supervised and semi-supervised models by making use of Python-based libraries such as scikit-learn. You will also discover practical applications for complex techniques such as maximum likelihood estimation, Hebbian learning, and ensem ...
Mastering Machine Learning Algorithms, 2nd Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and unsupervised learning domains. You will use all the modern libraries from the Python ecosystem - including NumPy and Keras - to extract features from varied complexities of data. Ranging from Bayesian models to the Markov chain Monte Carlo algorithm to Hidden Markov models, this machine learning book teaches you how to extract features from your dataset, perform complex dimensionality reduction, and train supervised and semi-supervised models by making use of Python-based libraries such as scikit-learn. You will also discover practical applications for complex techniques such as maximum likelihood estimation, Hebbian learning, and ensem ...
Functional Design Patterns for Express.js
Ready to design Node.js backends that scale elegantly with new features and are a pleasure to maintain? Learn to apply functional programming patterns that transcend Express.js - these ideas are found in exceptional production codebases of all kinds. Whether you're a seasoned back-end developer, front-end developer or recent web boot camp graduate, this step-by-step guide is for you. This work was written and produced entirely by the author. We are proud to be distributing it. Express is arguably the ubiquitous library for building Node backends. As of mid-2019, it is a dependency of 3.75 million codebases on Github alone. So if you hop into a Node codebase, chances are Express is part of it. Starting from an empty directory, we'll build a full-featured Express backend together and intentionally bump into codebase growing pains to motivate functional design patterns and Express features. With this book, you'll: Learn Express.js by building a pure backend with authenticatio ...
Ready to design Node.js backends that scale elegantly with new features and are a pleasure to maintain? Learn to apply functional programming patterns that transcend Express.js - these ideas are found in exceptional production codebases of all kinds. Whether you're a seasoned back-end developer, front-end developer or recent web boot camp graduate, this step-by-step guide is for you. This work was written and produced entirely by the author. We are proud to be distributing it. Express is arguably the ubiquitous library for building Node backends. As of mid-2019, it is a dependency of 3.75 million codebases on Github alone. So if you hop into a Node codebase, chances are Express is part of it. Starting from an empty directory, we'll build a full-featured Express backend together and intentionally bump into codebase growing pains to motivate functional design patterns and Express features. With this book, you'll: Learn Express.js by building a pure backend with authenticatio ...
Next-Generation Machine Learning with Spark
Access real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning applications. The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry. Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. Be introduced to machine learning, Spark, and Spark MLlib 2.4.x; Achieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM libraries; Detect anomalies with the Isolation Forest algorithm for Spark; Use the Spark NLP and Stanford CoreNLP lib ...
Access real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning applications. The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry. Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. Be introduced to machine learning, Spark, and Spark MLlib 2.4.x; Achieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM libraries; Detect anomalies with the Isolation Forest algorithm for Spark; Use the Spark NLP and Stanford CoreNLP lib ...
Machine Learning Yearning
AI is transforming numerous industries. Machine Learning Yearning, a free ebook from Andrew Ng, teaches you how to structure Machine Learning projects. This book is focused not on teaching you ML algorithms, but on how to make ML algorithms work. After reading Machine Learning Yearning, you will be able to: Prioritize the most promising directions for an AI project; Diagnose errors in a machine learning system; Build ML in complex settings, such as mismatched training/ test sets; Set up an ML project to compare to and/or surpass human - level performance; Know when and how to apply end-to-end learning, transfer learning, and multi-task learning. ...
AI is transforming numerous industries. Machine Learning Yearning, a free ebook from Andrew Ng, teaches you how to structure Machine Learning projects. This book is focused not on teaching you ML algorithms, but on how to make ML algorithms work. After reading Machine Learning Yearning, you will be able to: Prioritize the most promising directions for an AI project; Diagnose errors in a machine learning system; Build ML in complex settings, such as mismatched training/ test sets; Set up an ML project to compare to and/or surpass human - level performance; Know when and how to apply end-to-end learning, transfer learning, and multi-task learning. ...