This is the undisputed go-to guide to Rust, written by two members of the Rust core team, with feedback and contributions from 42 members of the community. The book assumes that you’ve written code in another programming language but makes no assumptions about which one, meaning the material is accessible and useful to developers from a wide variety of programming backgrounds.Known by the Rust community as "The Book," The Rust Programming Language includes concept chapters, where you’ll learn about a particular aspect of Rust, and project chapters, where you’ll apply what you’ve learned so far to build small programs.The Book opens with a quick hands-on project to introduce the basics then explores key concepts in depth, such as ownership, the type system, error handling, and fearless concurrency. Next come detailed explanations of Rust-oriented perspectives on topics like pattern matching, iterators, and smart pointers, with concrete examples and exercises--taking you from theory to practice.The Rust Programming Language will show you how to: Grasp important concepts unique to Rust like ownership, borrowing, and lifetimes Use Cargo, Rust’s built-in package manager, to build and maintain your code, including downloading and building dependencies Effectively use Rust’s zero-cost abstractions and employ your ownYou’ll learn to develop reliable code that’s speed and memory efficient, while avoiding the infamous and arcane programming pitfalls common at the systems level. When you need to dive down into lower-level control, this guide will show you how without taking on the customary risk of crashes or security holes and without requiring you to learn the fine points of a fickle toolchain.You’ll also learn how to create command line programs, build single- and multithreaded web servers, and much more.The Rust Programming Language fully embraces Rust’s potential to empower its users. This friendly and approachable guide will help you build not only your knowledge of Rust but also your ability to program with confidence in a wider variety of domains.

    You'll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, data visualizations with Python's super-handy libraries, and a simple web app you can deploy online.As you work through Python Crash Course, you'll learn how to: Use powerful Python libraries and tools, including matplotlib, NumPy, and PygalMake 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progressesWork with data to generate interactive visualizationsCreate and customize simple web apps and deploy them safely onlineDeal with mistakes and errors so you can solve your own programming problemsIf you've been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code!

    This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experience teaching the course at MIT since the first edition was published. A new theme has been introduced that emphasizes the central role played by different approaches to dealing with time in computational models: objects with state, concurrent programming, functional programming and lazy evaluation, and nondeterministic programming. There are new example sections on higher-order procedures in graphics and on applications of stream processing in numerical programming, and many new exercises. In addition, all the programs have been reworked to run in any Scheme implementation that adheres to the IEEE standard.

    Leading agile consultant and practitioner Mike Cohn presents detailed recommendations, powerful tips, and real-world case studies drawn from his unparalleled experience helping hundreds of software organizations make Scrum and agile work. "Succeeding with Agile" is for pragmatic software professionals who want real answers to the most difficult challenges they face in implementing Scrum. Cohn covers every facet of the transition: getting started, helping individuals transition to new roles, structuring teams, scaling up, working with a distributed team, and finally, implementing effective metrics and continuous improvement.Throughout, Cohn presents “Things to Try Now” sections based on his most successful advice. Complementary “Objection” sections reproduce typical conversations with those resisting change and offer practical guidance for addressing their concerns. Coverage includes: - Practical ways to get started immediately–and “get good” fast - Overcoming individual resistance to the changes Scrum requires - Staffing Scrum projects and building effective teams - Establishing “improvement communities” of people who are passionate about driving change - Choosing which agile technical practices to use or experiment with - Leading self-organizing teams - Making the most of Scrum sprints, planning, and quality techniques - Scaling Scrum to distributed, multiteam projects - Using Scrum on projects with complex sequential processes or challenging compliance and governance requirements - Understanding Scrum’s impact on HR, facilities, and project managementWhether you've completed a few sprints or multiple agile projects and whatever your role–manager, developer, coach, ScrumMaster, product owner, analyst, team lead, or project lead–this book will help you succeed with your very next project. Then, it will help you go much further: It will help you transform your entire development organization.

    Based on numerous interviews, this book reveals exclusive new information about how Apple innovates, deals with its suppliers, and is handling the transition into the post Jobs era.

    The Scrum Guide documents the Scrum framework and is maintained by Scrum’s creators, Ken Schwaber and Jeff Sutherland.

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

    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

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    This insightful collection of essays explore the business concerns that programmers face during the course of their careers--particularly those programmers who are small independent software vendors.Sink also covers issues like starting your own business, and then performing the hiring, marketing, and finances in a style that programmers understand, sprinkled with a touch of humor.

    It has sold 30,000 copies in each edition and will continue to reach a huge academic audience.In this renowned book, Everett M. Rogers, professor and chair of the Department of Communication & Journalism at the University of New Mexico, explains how new ideas spread via communication channels over time. Such innovations are initially perceived as uncertain and even risky. To overcome this uncertainty, most people seek out others like themselves who have already adopted the new idea. Thus the diffusion process consists of a few individuals who first adopt an innovation, then spread the word among their circle of acquaintances--a process which typically takes months or years. But there are exceptions: use of the Internet in the 1990s, for example, may have spread more rapidly than any other innovation in the history of humankind. Furthermore, the Internet is changing the very nature of diffusion by decreasing the importance of physical distance between people. The fifth edition addresses the spread of the Internet, and how it has transformed the way human beings communicate and adopt new ideas.

    Through four years of groundbreaking research, Dr. Nicole Forsgren, Jez Humble, and Gene Kim set out to find a way to measure software delivery performance—and what drives it—using rigorous statistical methods. This book presents both the findings and the science behind that research. Readers will discover how to measure the performance of their teams, and what capabilities they should invest in to drive higher performance.

    In Turing’s Cathedral, George Dyson focuses on a small group of men and women, led by John von Neumann at the Institute for Advanced Study in Princeton, New Jersey, who built one of the first computers to realize Alan Turing’s vision of a Universal Machine. Their work would break the distinction between numbers that mean things and numbers that do things—and our universe would never be the same. Using five kilobytes of memory (the amount allocated to displaying the cursor on a computer desktop of today), they achieved unprecedented success in both weather prediction and nuclear weapons design, while tackling, in their spare time, problems ranging from the evolution of viruses to the evolution of stars. Dyson’s account, both historic and prophetic, sheds important new light on how the digital universe exploded in the aftermath of World War II. The proliferation of both codes and machines was paralleled by two historic developments: the decoding of self-replicating sequences in biology and the invention of the hydrogen bomb. It’s no coincidence that the most destructive and the most constructive of human inventions appeared at exactly the same time.  How did code take over the world? In retracing how Alan Turing’s one-dimensional model became John von Neumann’s two-dimensional implementation, Turing’s Cathedral offers a series of provocative suggestions as to where the digital universe, now fully three-dimensional, may be heading next.

    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

    If you're looking for a book like that, put this one back on the shelf.Rework shows you a better, faster, easier way to succeed in business. Read it and you'll know why plans are actually harmful, why you don't need outside investors, and why you're better off ignoring the competition. The truth is, you need less than you think. You don't need to be a workaholic. You don't need to staff up. You don't need to waste time on paperwork or meetings. You don't even need an office. Those are all just excuses.  What you really need to do is stop talking and start working. This book shows you the way. You'll learn how to be more productive, how to get exposure without breaking the bank, and tons more counterintuitive ideas that will inspire and provoke you.With its straightforward language and easy-is-better approach, Rework is the perfect playbook for anyone who’s ever dreamed of doing it on their own. Hardcore entrepreneurs, small-business owners, people stuck in day jobs they hate, victims of "downsizing," and artists who don’t want to starve anymore will all find valuable guidance in these pages.