Exceptional Ruby: Master the Art of Handling Failure in Ruby


Avdi Grimm - 2011
    Writing code that handles unexpected errors and still works is really hard. Most of us learn by trial and error. This short book removes the uncertainty. With over 100 pages of content and dozens of working examples, you’ll learn everything from the mechanics of how exceptions work to how to design a robust failure management architecture for your app or library. Whether you are a Ruby novice or a seasoned veteran, Exceptional Ruby will help you write cleaner, more resilient Ruby code.

Information Architecture for the World Wide Web: Designing Large-Scale Web Sites


Peter Morville - 1998
    How do you present large volumes of information to people who need to find what they're looking for quickly? This classic primer shows information architects, designers, and web site developers how to build large-scale and maintainable web sites that are appealing and easy to navigate. The new edition is thoroughly updated to address emerging technologies -- with recent examples, new scenarios, and information on best practices -- while maintaining its focus on fundamentals. With topics that range from aesthetics to mechanics, Information Architecture for the World Wide Web explains how to create interfaces that users can understand right away. Inside, you'll find:* An overview of information architecture for both newcomers and experienced practitioners* The fundamental components of an architecture, illustrating the interconnected nature of these systems. Updated, with updates for tagging, folksonomies, social classification, and guided navigation* Tools, techniques, and methods that take you from research to strategy and design to implementation. This edition discusses blueprints, wireframes and the role of diagrams in the design phase* A series of short essays that provide practical tips and philosophical advice for those who work on information architecture* The business context of practicing and promoting information architecture, including recent lessons on how to handle enterprise architecture* Case studies on the evolution of two large and very different information architectures, illustrating best practices along the way* How do you document the rich interfaces of web applications? How do you design for multiple platforms and mobile devices? With emphasis on goals and approaches over tactics or technologies, this enormously popular book gives you knowledge about information architecture with a framework that allows you to learn new approaches -- and unlearn outmoded ones.

Growing Rails Applications in Practice


Henning Koch - 2014
    

New Programmer's Survival Manual


Joshua Carter - 2011
    You've got the programming chops, you're up on the latest tech, you're sitting at your workstation... now what? New Programmer's Survival Manual gives your career the jolt it needs to get going: essential industry skills to help you apply your raw programming talent and make a name for yourself. It's a no-holds-barred look at what really goes on in the office--and how to not only survive, but thrive in your first job and beyond. Programming at industry level requires new skills - you'll build programs that dwarf anything you've done on your own. This book introduces you to practices for working on large-scale, long-lived programs at a professional level of quality. You'll find out how to work efficiently with your current tools, and discover essential new tools. But the tools are only part of the story; you've got to get street-smart too. Succeeding in the corporate working environment requires its own savvy. You'll learn how to navigate the office, work with your teammates, and how to deal with other people outside of your department. You'll understand where you fit into the big picture and how you contribute to the company's success. You'll also get a candid look at the tougher aspects of the job: stress, conflict, and office politics. Finally, programming is a job you can do for the long haul. This book helps you look ahead to the years to come, and your future opportunities--either as a programmer or in another role you grow into. There's nothing quite like the satisfaction of shipping a product and knowing, "I built that." Whether you work on embedded systems or web-based applications, in trendy technologies or legacy systems, this book helps you get from raw skill to an accomplished professional.

Writing Solid Code


Steve Maguire - 1993
    Focus is on an in-depth analysis and exposition of not-so-obvious coding errors in the sample code provided. The theme is to answer the questions 'How couild I have automatically detected this bug' and 'How could I have prevented this bug'? Chapters include programmer attitudes, techniques and debugging methodology. A particularly revealing chapter is "Treacheries of the Trade", should be required reading for all C maniacs. The author has been a professional programmer for seventeen years and draws heavily (and candidly) on actual coding problems and practices based on years of experience at Microsoft.

The Nature of Code


Daniel Shiffman - 2012
    Readers will progress from building a basic physics engine to creating intelligent moving objects and complex systems, setting the foundation for further experiments in generative design. Subjects covered include forces, trigonometry, fractals, cellular automata, self-organization, and genetic algorithms. The book's examples are written in Processing, an open-source language and development environment built on top of the Java programming language. On the book's website (http://www.natureofcode.com), the examples run in the browser via Processing's JavaScript mode.

Hands-On Machine Learning with Scikit-Learn and TensorFlow


Aurélien Géron - 2017
    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

Working in Public: The Making and Maintenance of Open Source Software


Nadia Eghbal - 2020
    In the late 1990s, it provided an optimistic model for public

Programming in Objective-C 2.0


Stephen G. Kochan - 2008
    It includes detailed examples and exercises.

How to Design Programs: An Introduction to Programming and Computing


Matthias Felleisen - 2001
    Unlike other introductory books, it focuses on the program design process. This approach fosters a variety of skills--critical reading, analytical thinking, creative synthesis, and attention to detail--that are important for everyone, not just future computer programmers. The book exposes readers to two fundamentally new ideas. First, it presents program design guidelines that show the reader how to analyze a problem statement; how to formulate concise goals; how to make up examples; how to develop an outline of the solution, based on the analysis; how to finish the program; and how to test. Each step produces a well-defined intermediate product. Second, the book comes with a novel programming environment, the first one explicitly designed for beginners. The environment grows with the readers as they master the material in the book until it supports a full-fledged language for the whole spectrum of programming tasks.All the book's support materials are available for free on the Web. The Web site includes the environment, teacher guides, exercises for all levels, solutions, and additional projects.A second edition is now available.

Types and Programming Languages


Benjamin C. Pierce - 2002
    The study of type systems--and of programming languages from a type-theoretic perspective--has important applications in software engineering, language design, high-performance compilers, and security.This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material.The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.

Java Performance


Charlie Hunt - 2010
    

Deep Learning with Python


François Chollet - 2017
    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

CSS Secrets: Better Solutions to Everyday Web Design Problems


Lea Verou - 2014
    Based on two popular talks from author Lea Verou--including "CSS3 Secrets: 10 things you may not know about CSS"--this practical guide provides intermediate to advanced CSS developers with more than 40 undocumented techniques and tips for using CSS3 to create better websites.The talks that spawned this book have been top-rated by attendees in every conference they were presented, and praised in industry media such as ."net" magazine.Get information you won't find in any other bookLearn through small, easily digestible chaptersHelps you understand CSS more deeply so you can improve your own solutionsApply Lea's techniques to practically every CSS problem you faceGain tips from a rockstar author who serves as an Invited Expert in W3C's CSS Working Group