Bücher veröffentlicht von Pragmatic Bookshelf

Master machine learning by writing code one line at a time, from simple learning programs all the way to a true deep learning system. Tackle the hard topics by breaking them down so they're easier to understand, and build your confidence by getting your hands dirty.

Whether you want to automate tasks, analyze data, parse logs, talk to network services, or address other systems requirements, writing your own command-line tool may be the fastest - and perhaps the most fun - way to do it. The Go programming language is a great choice for developing tools that are fast, reliable, and cross-platform. Create command-line tools that work with files, connect to services, and even manage external processes, all while using tests and benchmarks to ensure your programs are fast and correct.When you want to develop cross platform command-line tools that are fast and reliable, use Go, a modern programming language that combines the reliability of compiled languages with the ease of use and flexibility of dynamic typed languages. Work through practical examples to develop elegant and efficient tools by applying Go's rich standard library, its built in support for concurrency, and its expressive syntax. Use Go's integrated testing capabilities to automatically test your tools, ensuring they work reliably even across code refactoring.Develop CLI tools that interact with your users by using common input/output patterns, including environment variables and flags. Handle files to read or persist data, and manipulate paths consistently in cross-platform scenarios. Control processes and handle signals, and use a benchmark driven approach and Go's concurrency primitives to create tools that perform well. Use powerful external libraries such as Cobra to create modern and flexible tools that handle subcommands, and develop tools that interact with databases, APIs, and network services. Finally, leverage what you learned by tackling additional challenges at the end of each chapter.What You Need:Go 1.8 or higher, an internet connection to download the example files and additional libraries, and a text editor to write your programs.

This book is a useful companion for anyone learning to write clean Java code. The authors introduce you to the fundamentals of becoming a software craftsman, by comparing pieces of problematic code with an improved version, to help you to develop a sense for clean code. This unique before-and-after approach teaches you to create clean Java code.

Are you working on a codebase where cost overruns, death marches, and heroic fights with legacy code monsters are the norm? Battle these adversaries with novel ways to identify and prioritize technical debt, based on behavioral data from how developers work with code. And that's just for starters. Because good code involves social design, as well as technical design, you can find surprising dependencies between people and code to resolve coordination bottlenecks among teams. Best of all, the techniques build on behavioral data that you already have: your version-control system. Join the fight for better code!Use statistics and data science to uncover both problematic code and the behavioral patterns of the developers who build your software. This combination gives you insights you can't get from the code alone. Use these insights to prioritize refactoring needs, measure their effect, find implicit dependencies between different modules, and automatically create knowledge maps of your system based on actual code contributions.In a radical, much-needed change from common practice, guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Discover a comprehensive set of practical analysis techniques based on version-control data, where each point is illustrated with a case study from a real-world codebase. Because the techniques are language neutral, you can apply them to your own code no matter what programming language you use. Guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Apply research findings from social psychology to software development, ensuring you get the tools you need to coach your organization towards better code.If you're an experienced programmer, software architect, or technical manager, you'll get a new perspective that will change how you work with code.What You Need:You don't have to install anything to follow along in the book. TThe case studies in the book use well-known open source projects hosted on GitHub. You'll use CodeScene, a free software analysis tool for open source projects, for the case studies. We also discuss alternative tooling options where they exist.