Coding Faster

Expert advice to help you work smarter and increase your productivity with Visual Studio. Take a detailed look into Visual Studio—and learn practical techniques to help you work more efficiently. This fully revised and expanded version of Visual Studio Tips: 251 Ways to Improve Your Productivity includes a comprehensive collection of tips and shortcuts for working with the code editor, visual designers, searches, debugger, and other features in Visual Studio 2005, 2008, and 2010. You'll gain valuable insights for using this IDE—no matter what your experience level. Discover how to: Change development settings and keyboard mappings to optimize your efficiency Save time initiating a new project by creating custom templates Uncover secrets for working with the toolbox, commands, and window layouts Work with files in more practical ways, such as using the File Tab Channel Use the Editor more effectively with tips on selecting and manipulating code Apply techniques to help reduce the time you spend debugging code Create Visual Studio extensions to increase your development productivity

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Efficient C/C++ Programming describes a practical, real-world approach to efficient C/C++ programming. Topics covered range from how to save storage using a restricted character set and how to speed up access to records by employing hash coding and caching. A selective mailing list system is used to illustrate rapid access to and rearrangement of information selected by criteria specified at runtime. Comprised of eight chapters, this book begins by discussing factors to consider when deciding whether a program needs optimization. In the next chapter, a supermarket price lookup system is used to illustrate how to save storage by using a restricted character set and how to speed up access to records with the aid of hash coding and caching. Attention is paid to rapid retrieval of prices. A selective mailing list system is then used to illustrate rapid access to and rearrangement of information selected by criteria specified at runtime. The book also considers the Huffman coding and arithmetic coding methods of data compression; a token-threaded interpreter whose code can run faster than equivalent compiled C code, due to its greater code density; a customer database program with variable-length records; and index and key access to variable-length records. The final chapter summarizes the characteristics of the algorithms encountered in previous chapters, as well as the future of the art of optimization. This monograph will be a useful resource for practicing computer programmers and those who intend to be working programmers.

This is a guide for creating readable, maintainable, reusable and faster code. No object oriented programming is involved. Out of all techniques which aim to improve your product's quality, readability has the highest return on effort. - Quality: Bugs are found mostly by reviewing other people's code. You can't review somebody else's code if you cannot read it. Bugs are not found by unit-tests, because unit-tests are created to capture errors that are known to exist. - Efficiency: Maintenance takes about 80% of developers' time. Therefore, spending some time in writing better code will save you more time during maintenance. - Performance: Unreadable code is difficult to reason about. Any opportunities for optimisation that may exist are often impossible to spot. The six techniques described are easy, therefore: - students can apply them - C programmers can follow it without changing programming paradigm - you can write idiomatic C++, instead of writing like C, Java, or Fortran.

Don't touch that mouse! Hands on the keyboard, and eyes front. You're about to embark on a Bootcamp to tone your coding muscles, sharpen your shortcuts, fix forms faster, and accelerate your career as a Delphi Programmer. Now drop and give me twenty lines of code and five laps of that while loop. This book will help you Code Faster in Delphi through a vast array of tips, tricks and hacks to squeeze every bit of productivity out of yourself and the Delphi IDE. Some ways your coding will be made easier: By enhancing the IDE with plugins. You'll be introduced to powerful language features such as: Interfaces Generics Anonymous Methods Get started with some of the best parts of the Run-Time Library, including: Generic Collections Parallel Programming Library Regular Expressions Enhanced RTTI FireDAC Use Meta-Programming to write and modify code to save you from horribly repetitive tasks. Improve your physical environment with easy solutions to hardware and station problems. And of course, once you've mastered these, where to go to get even faster and better. With over one hundred areas of improvement covered, this holistic approach to Coding Faster In Delphi will boost your productivity, and therefore your value to your clients, bosses, and colleagues.

Master professional-level coding in Rust. For developers who’ve mastered the basics, this book is the next step on your way to professional-level programming in Rust. It covers everything you need to build and maintain larger code bases, write powerful and flexible applications and libraries, and confidently expand the scope and complexity of your projects. Author Jon Gjengset takes you deep into the Rust programming language, dissecting core topics like ownership, traits, concurrency, and unsafe code. You’ll explore key concepts like type layout and trait coherence, delve into the inner workings of concurrent programming and asynchrony with async/await, and take a tour of the world of no_std programming. Gjengset also provides expert guidance on API design, testing strategies, and error handling, and will help develop your understanding of foreign function interfaces, object safety, procedural macros, and much more. You'll Learn: How to design reliable, idiomatic, and ergonomic Rust programs based on best principles Effective use of declarative and procedural macros, and the difference between them How asynchrony works in Rust – all the way from the Pin and Waker types used in manual implementations of Futures, to how async/await saves you from thinking about most of those words What it means for code to be unsafe, and best practices for writing and interacting with unsafe functions and traits How to organize and configure more complex Rust projects so that they integrate nicely with the rest of the ecosystem How to write Rust code that can interoperate with non-Rust libraries and systems, or run in constrained and embedded environments Brimming with practical, pragmatic insights that you can immediately apply, Rust for Rustaceans helps you do more with Rust, while also teaching you its underlying mechanisms.

Despite using them every day, most software engineers know little about how programming languages are designed and implemented. For many, their only experience with that corner of computer science was a terrifying "compilers" class that they suffered through in undergrad and tried to blot from their memory as soon as they had scribbled their last NFA to DFA conversion on the final exam. That fearsome reputation belies a field that is rich with useful techniques and not so difficult as some of its practitioners might have you believe. A better understanding of how programming languages are built will make you a stronger software engineer and teach you concepts and data structures you'll use the rest of your coding days. You might even have fun. This book teaches you everything you need to know to implement a full-featured, efficient scripting language. You'll learn both high-level concepts around parsing and semantics and gritty details like bytecode representation and garbage collection. Your brain will light up with new ideas, and your hands will get dirty and calloused. Starting from main(), you will build a language that features rich syntax, dynamic typing, garbage collection, lexical scope, first-class functions, closures, classes, and inheritance. All packed into a few thousand lines of clean, fast code that you thoroughly understand because you wrote each one yourself.

A walkthrough of computer science concepts you must know. Designed for readers who don't care for academic formalities, it's a fast and easy computer science guide. It teaches the foundations you need to program computers effectively. After a simple introduction to discrete math, it presents common algorithms and data structures. It also outlines the principles that make computers and programming languages work.