How To Code in React.js
This open book is an introduction to React that works from the foundations upward. Each chapter takes you a little deeper into the React ecosystem, building on your previous knowledge. Along the way, you'll learn how to maintain internal state, pass information between parts of an application, and explore different options for styling your application. Whether you are completely new to React or if you've worked with it before, this series will be accessible to you. Every chapter is self contained, so you can jump between chapters or skip whole sections. The book is designed for you to take a concept and explore it by building a small project that mirrors what you will encounter in everyday development using React. ...
This open book is an introduction to React that works from the foundations upward. Each chapter takes you a little deeper into the React ecosystem, building on your previous knowledge. Along the way, you'll learn how to maintain internal state, pass information between parts of an application, and explore different options for styling your application. Whether you are completely new to React or if you've worked with it before, this series will be accessible to you. Every chapter is self contained, so you can jump between chapters or skip whole sections. The book is designed for you to take a concept and explore it by building a small project that mirrors what you will encounter in everyday development using React. ...
Tableau Strategies
If you want to increase Tableau's value to your organization, this practical book has your back. Authors Ann Jackson and Luke Stanke guide data analysts through strategies for solving real-world analytics problems using Tableau. Starting with the basics and building toward advanced topics such as multidimensional analysis and user experience, you'll explore pragmatic and creative examples that you can apply to your own data. Staying competitive today requires the ability to quickly analyze and visualize data and make data-driven decisions. With this guide, data practitioners and leaders alike will learn strategies for building compelling and purposeful visualizations, dashboards, and data products. Every chapter contains the why behind the solution and the technical knowledge you need to make it work. Use this book as a high-value on-the-job reference guide to Tableau; Visualize different data types and tackle specific data challenges; Create compelling data visualizations, dashb ...
If you want to increase Tableau's value to your organization, this practical book has your back. Authors Ann Jackson and Luke Stanke guide data analysts through strategies for solving real-world analytics problems using Tableau. Starting with the basics and building toward advanced topics such as multidimensional analysis and user experience, you'll explore pragmatic and creative examples that you can apply to your own data. Staying competitive today requires the ability to quickly analyze and visualize data and make data-driven decisions. With this guide, data practitioners and leaders alike will learn strategies for building compelling and purposeful visualizations, dashboards, and data products. Every chapter contains the why behind the solution and the technical knowledge you need to make it work. Use this book as a high-value on-the-job reference guide to Tableau; Visualize different data types and tackle specific data challenges; Create compelling data visualizations, dashb ...
OpenShift for Developers, 2nd Edition
Ready to build cloud native applications? Get a hands-on introduction to daily life as a developer crafting code on OpenShift, the open source container application platform from Red Hat. Creating and packaging your apps for deployment on modern distributed systems can be daunting. Too often, adding infrastructure value can complicate development. With this practical guide, you'll learn how to build, deploy, and manage a multitiered application on OpenShift. Authors Joshua Wood and Brian Tannous demonstrate how OpenShift speeds application development. With the Kubernetes container orchestrator at its core, OpenShift simplifies and automates the way you build, ship, and run code. You'll learn how to use OpenShift and the Quarkus Java framework to develop and deploy apps using proven enterprise technologies and practices that you can apply to code in any language. Learn the development cycles for building and deploying on OpenShift, and the tools that drive them; Use OpenShift to ...
Ready to build cloud native applications? Get a hands-on introduction to daily life as a developer crafting code on OpenShift, the open source container application platform from Red Hat. Creating and packaging your apps for deployment on modern distributed systems can be daunting. Too often, adding infrastructure value can complicate development. With this practical guide, you'll learn how to build, deploy, and manage a multitiered application on OpenShift. Authors Joshua Wood and Brian Tannous demonstrate how OpenShift speeds application development. With the Kubernetes container orchestrator at its core, OpenShift simplifies and automates the way you build, ship, and run code. You'll learn how to use OpenShift and the Quarkus Java framework to develop and deploy apps using proven enterprise technologies and practices that you can apply to code in any language. Learn the development cycles for building and deploying on OpenShift, and the tools that drive them; Use OpenShift to ...
Data Science at the Command Line, 2nd Edition
This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools-useful whether you work with Windows, macOS, or Linux. You'll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you're comfortable processing data with Python or R, you'll learn how to greatly improve your data science workflow by leveraging the command line's power. This book is ideal for data scientists, analysts, engineers, system administrators, and researchers. Obtain data from websites, APIs, databases, and spreadsheets; Perform scrub operations on text, CSV, HTM, XML, and JSON files; Explore data, compute descriptive statistics, and create visualizations; M ...
This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools-useful whether you work with Windows, macOS, or Linux. You'll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you're comfortable processing data with Python or R, you'll learn how to greatly improve your data science workflow by leveraging the command line's power. This book is ideal for data scientists, analysts, engineers, system administrators, and researchers. Obtain data from websites, APIs, databases, and spreadsheets; Perform scrub operations on text, CSV, HTM, XML, and JSON files; Explore data, compute descriptive statistics, and create visualizations; M ...
React Cookbook
React helps you create and work on an app in just a few minutes. But learning how to put all the pieces together is hard. How do you validate a form? Or implement a complex multistep user action without writing messy code? How do you test your code? Make it reusable? Wire it to a backend? Keep it easy to understand? The React Cookbook delivers answers fast. Many books teach you how to get started, understand the framework, or use a component library with React, but very few provide examples to help you solve particular problems. This easy-to-use cookbook includes the example code developers need to unravel the most common problems when using React, categorized by topic area and problem. You'll learn how to: Build a single-page application in React using a rich UI; Create progressive web applications that users can install and work with offline; Integrate with backend services such as REST and GraphQL; Automatically test for accessibility problems in your application; Secure appli ...
React helps you create and work on an app in just a few minutes. But learning how to put all the pieces together is hard. How do you validate a form? Or implement a complex multistep user action without writing messy code? How do you test your code? Make it reusable? Wire it to a backend? Keep it easy to understand? The React Cookbook delivers answers fast. Many books teach you how to get started, understand the framework, or use a component library with React, but very few provide examples to help you solve particular problems. This easy-to-use cookbook includes the example code developers need to unravel the most common problems when using React, categorized by topic area and problem. You'll learn how to: Build a single-page application in React using a rich UI; Create progressive web applications that users can install and work with offline; Integrate with backend services such as REST and GraphQL; Automatically test for accessibility problems in your application; Secure appli ...
Front-end Developer Handbook
This is a guide that everyone can use to learn about the practice of front-end development. It broadly outlines and discusses the practice of front-end engineering: how to learn it and what tools are used when practicing. It is specifically written with the intention of being a professional resource for potential and currently practicing front-end developers to equip themselves with learning materials and development tools. Secondarily, it can be used by managers, CTOs, instructors, and head hunters to gain insights into the practice of front-end development.The content of the handbook favors web technologies (HTML, CSS, DOM, and JavaScript) and those solutions that are directly built on top of these open technologies. The materials referenced and discussed in the book are either best in class or the current offering to a problem. ...
This is a guide that everyone can use to learn about the practice of front-end development. It broadly outlines and discusses the practice of front-end engineering: how to learn it and what tools are used when practicing. It is specifically written with the intention of being a professional resource for potential and currently practicing front-end developers to equip themselves with learning materials and development tools. Secondarily, it can be used by managers, CTOs, instructors, and head hunters to gain insights into the practice of front-end development.The content of the handbook favors web technologies (HTML, CSS, DOM, and JavaScript) and those solutions that are directly built on top of these open technologies. The materials referenced and discussed in the book are either best in class or the current offering to a problem. ...
Human-in-the-Loop Machine Learning
Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms. Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process. Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-Loop Machine Learning lays out methods for humans and machines to work together effectively. You'll find best pra ...
Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms. Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process. Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-Loop Machine Learning lays out methods for humans and machines to work together effectively. You'll find best pra ...
Transfer Learning for Natural Language Processing
Training deep learning NLP models from scratch is costly, time-consuming, and requires massive amounts of data. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre reveals cutting-edge transfer learning techniques that apply customizable pretrained models to your own NLP architectures. You'll learn how to use transfer learning to deliver state-of-the-art results for language comprehension, even when working with limited label data. Best of all, you'll save on training time and computational costs. Build custom NLP models in record time, even with limited datasets! Transfer learning is a machine learning technique for adapting pretrained machine learning models to solve specialized problems. This powerful approach has revolutionized natural language processing, driving improvements in machine translation, business analytics, and natural language generation. Transfer Learning for Natural Language Processing teaches you to create powerful NLP solutions ...
Training deep learning NLP models from scratch is costly, time-consuming, and requires massive amounts of data. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre reveals cutting-edge transfer learning techniques that apply customizable pretrained models to your own NLP architectures. You'll learn how to use transfer learning to deliver state-of-the-art results for language comprehension, even when working with limited label data. Best of all, you'll save on training time and computational costs. Build custom NLP models in record time, even with limited datasets! Transfer learning is a machine learning technique for adapting pretrained machine learning models to solve specialized problems. This powerful approach has revolutionized natural language processing, driving improvements in machine translation, business analytics, and natural language generation. Transfer Learning for Natural Language Processing teaches you to create powerful NLP solutions ...
Deep Learning Patterns and Practices
The big challenge of deep learning lies in taking cutting-edge technologies from R&D labs through to production. Deep Learning Patterns and Practices is here to help. This unique guide lays out the latest deep learning insights from author Andrew Ferlitsch's work with Google Cloud AI. In it, you'll find deep learning models presented in a unique new way: as extendable design patterns you can easily plug-and-play into your software projects. Each valuable technique is presented in a way that's easy to understand and filled with accessible diagrams and code samples. Discover best practices, design patterns, and reproducible architectures that will guide your deep learning projects from the lab into production. This awesome book collects and illuminates the most relevant insights from a decade of real world deep learning experience. You'll build your skills and confidence with each interesting example. Deep Learning Patterns and Practices is a deep dive into building successful deep ...
The big challenge of deep learning lies in taking cutting-edge technologies from R&D labs through to production. Deep Learning Patterns and Practices is here to help. This unique guide lays out the latest deep learning insights from author Andrew Ferlitsch's work with Google Cloud AI. In it, you'll find deep learning models presented in a unique new way: as extendable design patterns you can easily plug-and-play into your software projects. Each valuable technique is presented in a way that's easy to understand and filled with accessible diagrams and code samples. Discover best practices, design patterns, and reproducible architectures that will guide your deep learning projects from the lab into production. This awesome book collects and illuminates the most relevant insights from a decade of real world deep learning experience. You'll build your skills and confidence with each interesting example. Deep Learning Patterns and Practices is a deep dive into building successful deep ...
Full Stack Python Security
Full Stack Python Security: Cryptography, TLS, and attack resistance teaches you everything you'll need to build secure Python web applications. As you work through the insightful code snippets and engaging examples, you'll put security standards, best practices, and more into action. Along the way, you'll get exposure to important libraries and tools in the Python ecosystem. Security is a full-stack concern, encompassing user interfaces, APIs, web servers, network infrastructure, and everything in between. Master the powerful libraries, frameworks, and tools in the Python ecosystem and you can protect your systems top to bottom. Packed with realistic examples, lucid illustrations, and working code, this book shows you exactly how to secure Python-based web applications. Full Stack Python Security: Cryptography, TLS, and attack resistance teaches you everything you need to secure Python and Django-based web apps. In it, seasoned security pro Dennis Byrne demystifies complex secur ...
Full Stack Python Security: Cryptography, TLS, and attack resistance teaches you everything you'll need to build secure Python web applications. As you work through the insightful code snippets and engaging examples, you'll put security standards, best practices, and more into action. Along the way, you'll get exposure to important libraries and tools in the Python ecosystem. Security is a full-stack concern, encompassing user interfaces, APIs, web servers, network infrastructure, and everything in between. Master the powerful libraries, frameworks, and tools in the Python ecosystem and you can protect your systems top to bottom. Packed with realistic examples, lucid illustrations, and working code, this book shows you exactly how to secure Python-based web applications. Full Stack Python Security: Cryptography, TLS, and attack resistance teaches you everything you need to secure Python and Django-based web apps. In it, seasoned security pro Dennis Byrne demystifies complex secur ...