Front-end Developer HandbookThis 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. ...
Good Code, Bad CodeThe difference between good code or bad code often comes down to how you apply the established practices of the software development community. In Good Code, Bad Code you'll learn how to boost your productivity and effectiveness with code development insights normally only learned through careful mentorship and hundreds of code reviews.
Software development is a team sport. For an application to succeed, your code needs to be robust and easy for others to understand, maintain, and adapt. Whether you're working on an enterprise team, contributing to an open source project, or bootstrapping a startup, it pays to know the difference between good code and bad code.
Good Code, Bad Code is a clear, practical introduction to writing code that's a snap to read, apply, and remember. With dozens of instantly-useful techniques, you'll find coding insights that normally take years of experience to master. In this fast-paced guide, Google software engineer Tom Long teaches you a host of rules ...
Software TelemetrySoftware Telemetry teaches you best practices for operating and updating telemetry systems. These vital systems trace, log, and monitor infrastructure by observing and analyzing the events generated by the system. This practical guide is filled with techniques you can apply to any size of organization, with troubleshooting techniques for every eventuality, and methods to ensure your compliance with standards like GDPR.
Take advantage of the data generated by your IT infrastructure! Telemetry systems provide feedback on what's happening inside your data center and applications, so you can efficiently monitor, maintain, and audit them. This practical book guides you through instrumenting your systems, setting up centralized logging, doing distributed tracing, and other invaluable telemetry techniques.
Software Telemetry shows you how to efficiently collect, store, and analyze system and application log data so you can monitor and improve your systems. Manage the pillars of observab ...
Data Engineering on AzureData Engineering on Azure reveals the data management patterns and techniques that support Microsoft's own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning.
Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify.
In Data Engineering on Azure you'll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, p ...
Deep Learning Patterns and PracticesThe 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 ...
Rust in ActionRust in Action introduces the Rust programming language by exploring numerous systems programming concepts and techniques. You'll be learning Rust by delving into how computers work under the hood. You'll find yourself playing with persistent storage, memory, networking and even tinkering with CPU instructions. The book takes you through using Rust to extend other applications and teaches you tricks to write blindingly fast code. You'll also discover parallel and concurrent programming. Filled to the brim with real-life use cases and scenarios, you'll go beyond the Rust syntax and see what Rust has to offer in real-world use cases.
Rust is the perfect language for systems programming. It delivers the low-level power of C along with rock-solid safety features that let you code fearlessly. Ideal for applications requiring concurrency, Rust programs are compact, readable, and blazingly fast. Best of all, Rust's famously smart compiler helps you avoid even subtle coding errors.
Rust ...
App Modernization on Azure SuccinctlyWhat's the right way to move existing applications to the cloud to better use its power while enabling new features? In App Modernization on Azure Succinctly, Lorenzo Barbieri will help you understand how to modernize existing apps without completely rewriting them. This ebook will guide you through moving your app to the cloud, refactoring, rearchitecting, and choosing which cloud services will improve your app and experience. Most of the concepts in this book are also valid for a complete rewrite of an app directly in the cloud, or new apps built directly in the cloud. ...
Financial Theory with PythonNowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance.
Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other.
Draw upon mathematics to learn the foundations of financial theory and Python programming; Learn about financial theory, financial data modeling, and the use of Python for computational finance; Leverage simple economic models to better understand basic notions of finance and Python programming co ...
Multithreaded JavaScriptTraditionally, JavaScript has been a single-threaded language. Nearly all online forum posts, books, online documentation, and libraries refer to the language as single threaded. Thanks to recent advancements in the language-such as the Atomics and SharedArrayBuffers objects and Web Workers in the browser-JavaScript is now a multi-threaded language. These features will go down as being the biggest paradigm shift for the world's most popular programming language.
Multithreaded JavaScript explores the various features that JavaScript runtimes have at their disposal for implementing multithreaded programming, providing both practical real-world examples, as well as reference material.
Learn what multithreaded programming is and how you can benefit from it; Understand the differences between a web worker, a service worker, and a worker thread; Know when and when not to use threads in an application; Orchestrate communication between threads by leveraging the Atomics object; Build hig ...
Practical Weak SupervisionMost data scientists and engineers today rely on quality labeled data to train machine learning models. But building a training set manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Wee Hyong Tok, Amit Bahree, and Senja Filipi show you how to create products using weakly supervised learning models.
You'll learn how to build natural language processing and computer vision projects using weakly labeled datasets from Snorkel, a spin-off from the Stanford AI Lab. Because so many companies have pursued ML projects that never go beyond their labs, this book also provides a guide on how to ship the deep learning models you build.
Get up to speed on the field of weak supervision, including ways to use it as part of the data science process; Use Snorkel AI for weak supervision and data programming; Get code examples for using Snorkel to label text and image datasets; Use a weakly labeled dataset f ...