Pragmatic programmers okt 2024 (2 Ergebnisse)

Taschenbuch. Zustand: Neu. Neuware - Turn your React project requirements into tests and get the feedback you need faster than ever before. Combine the power of testing, linting, and typechecking directly in your coding environment to iterate on React components quickly and fearlessly!You work in a loop: write code, get feedback, adjust. The faster you get feedback, the faster your code improves and the more effective you become as a developer. And that feedback comes from testing.The conceptual elegance of React has opened the door to a new generation of web testing: clear, expressive, and lightning fast. That makes React a perfect fit for test-driven development (TDD), a methodology in which tests are a blueprint instead of an afterthought.Each chapter presents new projects to challenge you and new tools to help you:- Write fast, easy-to-understand tests with Vitest and React Testing Library.- Keep your code tidy with ESLint and Prettier.- Perform every task you need from a single window within VS Code. - See your test output directly in your code with Wallaby.- Style components in a test-friendly way with styled-components. - Stay focused on what's important by running your tests continuously in the background.- Generate beautiful documentation with Storybook, and update it on every commit with GitHub Actions.The second edition of Test-Driven React has been extensively revised to reflect the latest tools and techniques for React development, including TypeScript. Each chapter presents new projects to challenge you and new tools to help you find and fix type errors without even running your code.What You Need:You'll need a working knowledge of JavaScript or TypeScript, and a computer running macOS, Windows, or Linux.…

Taschenbuch. Zustand: Neu. Neuware - Stable Diffusion, ChatGPT, Whisper - these are just a few examples of incredible applications powered by developments in machine learning. Despite the ubiquity of machine learning applications running in production, there are only a few viable language choices for data science and machine learning tasks. Elixir's Nx project seeks to change that. With Nx, you can leverage the power of machine learning in your applications, using the battle-tested Erlang VM in a pragmatic language like Elixir. In this book, you'll learn how to leverage Elixir and the Nx ecosystem to solve real-world problems in computer vision, natural language processing, and more.The Elixir Nx project aims to make machine learning possible without the need to leave Elixir for solutions in other languages. And even if concepts like linear models and logistic regression are new to you, you'll be using them and much more to solve real-world problems in no time.Start with the basics of the Nx programming paradigm - how it differs from the Elixir programming style you're used to and how it enables you to write machine learning algorithms. Use your understanding of this paradigm to implement foundational machine learning algorithms from scratch. Go deeper and discover the power of deep learning with Axon. Unlock the power of Elixir and learn how to build and deploy machine learning models and pipelines anywhere. Learn how to analyze, visualize, and explain your data and models.Discover how to use machine learning to solve diverse problems from image recognition to content recommendation - all in your favorite programming language.What You Need:You'll need a computer with a working installation of Elixir v1.12 and Erlang/OTP 24. For some of the more compute intensive examples, you'll want to use EXLA, which currently only supports x86-64 platforms. While not explicitly required, some examples will demonstrate programs running on accelerators such as CUDA/ROCm enabled GPUs and Google TPUs. Most of these programs will still run fine on a regular CPU, just for much longer periods of time.…