Game Engine Architecture


Jason Gregory - 2009
    The concepts and techniques described are the actual ones used by real game studios like Electronic Arts and Naughty Dog. The examples are often grounded in specific technologies, but the discussion extends way beyond any particular engine or API. The references and citations make it a great jumping off point for those who wish to dig deeper into any particular aspect of the game development process.Intended as the text for a college level series in game programming, this book can also be used by amateur software engineers, hobbyists, self-taught game programmers, and existing members of the game industry. Junior game engineers can use it to solidify their understanding of game technology and engine architecture. Even senior engineers who specialize in one particular field of game development can benefit from the bigger picture presented in these pages.

JavaScript & jQuery: The Missing Manual


David Sawyer McFarland - 2008
    This jargon-free guide covers JavaScript basics and shows you how to save time and effort with the jQuery library of prewritten JavaScript code. You’ll soon be building web pages that feel and act like desktop programs, without having to do much programming.The important stuff you need to know:Make your pages interactive. Create JavaScript events that react to visitor actions.Use animations and effects. Build drop-down navigation menus, pop-ups, automated slideshows, and more.Improve your user interface. Learn how the pros make websites fun and easy to use.Collect data with web forms. Create easy-to-use forms that ensure more accurate visitor responses.Add a dash of Ajax. Enable your web pages to communicate with a web server without a page reload.Practice with living examples. Get step-by-step tutorials for web projects you can build yourself.

The Myths of Innovation


Scott Berkun - 2007
    We depend more than we realize on wishful thinking and romanticized ideas of history. In the new paperback edition of this fascinating book, a book that has appeared on MSNBC, CNBC, Slashdot.org, Lifehacker.com and in The New York Times, bestselling author Scott Berkun pulls the best lessons from the history of innovation, including the recent software and web age, to reveal powerful and suprising truths about how ideas become successful innovations -- truths people can easily apply to the challenges of today. Through his entertaining and insightful explanations of the inherent patterns in how Einstein’s discovered E=mc2 or Tim Berner Lee’s developed the idea of the world wide web, you will see how to develop existing knowledge into new innovations.Each entertaining chapter centers on breaking apart a powerful myth, popular in the business world despite it's lack of substance. Through Berkun's extensive research into the truth about innovations in technology, business and science, you’ll learn lessons from the expensive failures and dramatic successes of innovations past, and understand how innovators achieved what they did -- and what you need to do to be an innovator yourself. You'll discover:Why problems are more important than solutionsHow the good innovation is the enemy of the greatWhy children are more creative than your co-workersWhy epiphanies and breakthroughs always take timeHow all stories of innovations are distorted by the history effectHow to overcome people’s resistance to new ideasWhy the best idea doesn’t often winThe paperback edition includes four new chapters, focused on appling the lessons from the original book, and helping you develop your skills in creative thinking, pitching ideas, and staying motivated."For centuries before Google, MIT, and IDEO, modern hotbeds of innovation, we struggled to explain any kind of creation, from the universe itself to the multitudes of ideas around us. While we can make atomic bombs, and dry-clean silk ties, we still don’t have satisfying answers for simple questions like: Where do songs come from? Are there an infinite variety of possible kinds of cheese? How did Shakespeare and Stephen King invent so much, while we’re satisfied watching sitcom reruns? Our popular answers have been unconvincing, enabling misleading, fantasy-laden myths to grow strong." -- Scott Berkun, from the text"Berkun sets us free to change the world." -- Guy Kawasaki, author of Art of the StartScott was a manager at Microsoft from 1994-2003, on projects including v1-5 (not 6) of Internet Explorer. He is the author of three bestselling books, Making Things Happen, The Myths of Innovation and Confessions of a Public Speaker. He works full time as a writer and speaker, and his work has appeared in The New York Times, Forbes magazine, The Economist, The Washington Post, Wired magazine, National Public Radio and other media. He regularly contributes to Harvard Business Review and Bloomberg Businessweek, has taught creative thinking at the University of Washington, and has appeared as an innovation and management expert on MSNBC and on CNBC. He writes frequently on innovation and creative thinking at his blog: scottberkun.com and tweets at @berkun.

Signal Processing and Linear Systems


B.P. Lathi - 2000
    Based on B. P. Lathi's widely used book, Linear Systems and Signals, it features additional applications to communications, controls, and filtering as well as new chapters on analog and digital filters and digital signal processing. Lathi emphasizes the physical appreciation of concepts rather than the mere mathematical manipulation of symbols. Avoiding the tendency to treat engineering as a branch of applied mathematics, he uses mathematics to enhance physical and intuitive understanding of concepts, instead of employing it only to prove axiomatic theory. Theoretical results are supported by carefully chosen examples and analogies, allowing students to intuitively discover meaning for themselves.

The Decline and Fall of IBM: End of an American Icon?


Robert Cringely - 2014
    Big Blue, as the company is known, tends to rely for its success on magical thinking but that magic ran out a long time ago. The company got in trouble back in the 1990s and had to hire for the first time an outside CEO, Lou Gerstner, to save the day. Gerstner pushed IBM into services with spectacular results but this hurt the company, too. As services have became commoditized IBM could only compete by offshoring the work and quality suffered. The other negative impact of Gerstner was his compensation which was for the first time in IBM history very high. Only the Watson family had become rich running IBM with later CEOs like John Opel and John Akers living comfortable lives with lots of perks, but they never got BIG RICH. That changed with Gerstner. Sam Palmisano an IBM lifer followed Gerstner as CEO and followed, too, the Gerstner playbook. Palmisano retired three years ago with a retirement package worth $241 million, replaced by IBM's first woman CEO, Ginni Rometty, who certainly expects a comparable golden parachute. In order to achieve these numbers, though, IBM has essentially sacrificed both its customers and employees. In order to have ever growing earnings per share the company has cut labor to the bone, off-shored everything it can, dropped quality, deliberately underbid contracts to win them then not performed. IBM's acquisition policy is one of buying companies to get their sales then cutting costs to the bone and under-delivering. This and share buybacks have kept earnings growing until this house of cards recently began to fall. Ginni Rometty, who will end up taking the fall for Palmisano's flawed strategy, has stated a very specific earnings goal for 2015 that she will destroy the company to achieve if she must. This book how IBM fell from grace, where it is headed, and what specifically can be done to save the company before it is too late.

Data Science from Scratch: First Principles with Python


Joel Grus - 2015
    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

The Kubernetes Book: Version 2.2 - January 2018


Nigel Poulton - 2017
    Kubernetes has emerged as the hottest and most important container orchestration platform in the world. This book gets you up to speed fast, and it's constantly kept up-to-date!

Getting Real: The Smarter, Faster, Easier Way to Build a Web Application


37 Signals - 2006
    At under 200 pages it's quick reading too. Makes a great airplane book.

Designing the Internet of Things


Adrian McEwen - 2013
    If you'd like to create the next must-have product, this unique book is the perfect place to start.Both a creative and practical primer, it explores the platforms you can use to develop hardware or software, discusses design concepts that will make your products eye-catching and appealing, and shows you ways to scale up from a single prototype to mass production.Helps software engineers, web designers, product designers, and electronics engineers start designing products using the Internet-of-Things approach Explains how to combine sensors, servos, robotics, Arduino chips, and more with various networks or the Internet, to create interactive, cutting-edge devices Provides an overview of the necessary steps to take your idea from concept through production If you'd like to design for the future, Designing the Internet of Things is a great place to start.

Think Stats


Allen B. Downey - 2011
    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

Data Science at the Command Line: Facing the Future with Time-Tested Tools


Jeroen Janssens - 2014
    You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.To get you started--whether you're on Windows, OS X, or Linux--author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.Discover why the command line is an agile, scalable, and extensible technology. Even if you're already comfortable processing data with, say, Python or R, you'll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms

Two Scoops of Django: Best Practices for Django 1.5


Daniel Roy Greenfeld - 2013
    We'll introduce you to various tips, tricks, patterns, code snippets, and techniques that we've picked up over the years.This book is great for:Beginners who have just finished the Django tutorial.Developers with intermediate knowledge of Django who want to improve their Django projects.

Introducing Microsoft Power BI


Alberto Ferrari - 2016
    Stay in the know, spot trends as they happen, and push your business to new limits. This e-book introduces Microsoft Power BI basics through a practical, scenario-based guided tour of the tool, showing you how to build analytical solutions using Power BI. Get an overview of Power BI, or dig deeper and follow along on your PC using the book's examples.

The Language of SQL


Larry Rockoff - 2010
    For SQL beginners, it's more important for a book to focus on general concepts and offer clear explanations and examples of what the various statements can accomplish. This is that beginner book. A number of features make The LANGUAGE OF SQL unique among introductory SQL books. First, you will not be required to download software or sit with a computer as you read the text. The intent of this book is to provide examples of SQL usage that can be understood simply by reading them. Second, topics are organized in an intuitive and logical sequence. SQL keywords are introduced one at a time, allowing you to build on your prior understanding as you encounter new words and concepts. Finally, this book covers the syntax of three widely used databases: Microsoft SQL Server, MySQL, and Oracle, with special "Database Differences" boxes that will show you any differences in the syntax among those three databases, as well as instructions on how to obtain and install free versions of the databases. This is the only book you'll need to gain a working knowledge of SQL and relational databases.

Scalable and Modular Architecture for CSS


Jonathan Snook - 2011
    There is no library within here for you to download or install. SMACSS is a way to examine your design process and as a way to fit those rigid frameworks into a flexible thought process. It is an attempt to document a consistent approach to site development when using CSS. And really, who isn’t building a site with CSS these days?!Get to know Scalable and Modular Architecture for CSS