The Quick Python Book


Naomi R. Ceder - 2000
    This updated edition includes all the changes in Python 3, itself a significant shift from earlier versions of Python.The book begins with basic but useful programs that teach the core features of syntax, control flow, and data structures. It then moves to larger applications involving code management, object-oriented programming, web development, and converting code from earlier versions of Python.True to his audience of experienced developers, the author covers common programming language features concisely, while giving more detail to those features unique to Python.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

Learning Python


Mark Lutz - 2003
    Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.

Programming in C


Stephen G. Kochan - 2004
    Stephen Kochan's "Programming in C" is thorough with easy-to-follow instructions that are sure to benefit beginning programmers. This book provides readers with practical examples of how the C programming language can be used with small, fast programs, similar to the programming used by large game developers such as Nintendo. If you want a one-stop-source for C programming, this book is it.The book is appropriate for all introductory-to-intermediate courses on programming in the C language, including courses covering C programming for games and small-device platforms. "Programming in C, Third Edition" is a thoroughly revised and updated edition of Steven Kochan's classic C programming tutorial: a book that has helped thousands of students master C over the past twenty years. This edition fully reflects the latest C standard and contains current source code. It has been crafted to help students master C regardless of the platform they intend to use or the applications they intend to create -- including small-device and gaming applications, where C's elegance and speed make it especially valuable.Kochan begins with the fundamentals, then covers every facet of C language programming: variables, data types, arithmetic expressions, program looping, making decisions, arrays, functions, structures, character strings, pointers, operations on bits, the preprocessors, I/O, and more. Coverage also includes chapters on working with larger programs; debugging programs; and the fundamentals of object-oriented programming. Appendices include a complete language summary, an introduction to the Standard C Library, coverage of compiling and running programs using gcc, common programming mistakes, and more.

The Essential Turing: Seminal Writings in Computing, Logic, Philosophy, Artificial Intelligence, and Artificial Life Plus the Secrets of Enigma


Alan Turing - 2004
    In 1935, aged 22, he developed the mathematical theory upon which all subsequent stored-program digital computers are modeled.At the outbreak of hostilities with Germany in September 1939, he joined the Government Codebreaking team at Bletchley Park, Buckinghamshire and played a crucial role in deciphering Engima, the code used by the German armed forces to protect their radio communications. Turing's work on the versionof Enigma used by the German navy was vital to the battle for supremacy in the North Atlantic. He also contributed to the attack on the cyphers known as Fish, which were used by the German High Command for the encryption of signals during the latter part of the war. His contribution helped toshorten the war in Europe by an estimated two years.After the war, his theoretical work led to the development of Britain's first computers at the National Physical Laboratory and the Royal Society Computing Machine Laboratory at Manchester University.Turing was also a founding father of modern cognitive science, theorizing that the cortex at birth is an unorganized machine which through training becomes organized into a universal machine or something like it. He went on to develop the use of computers to model biological growth, launchingthe discipline now referred to as Artificial Life.The papers in this book are the key works for understanding Turing's phenomenal contribution across all these fields. The collection includes Turing's declassified wartime Treatise on the Enigma; letters from Turing to Churchill and to codebreakers; lectures, papers, and broadcasts which opened upthe concept of AI and its implications; and the paper which formed the genesis of the investigation of Artifical Life.

Physics for Scientists and Engineers


Douglas C. Giancoli - 1988
    For the calculus-based General Physics course primarily taken by engineers and scientists.

C# 5.0 in a Nutshell: The Definitive Reference


Joseph Albahari - 2012
    Uniquely organized around concepts and use cases, this updated fifth edition features a reorganized section on concurrency, threading, and parallel programming—including in-depth coverage of C# 5.0’s new asynchronous functions.Shaped by more than 20 expert reviewers, including Microsoft’s Eric Lippert, Stephen Toub, Chris Burrows, and Jon Skeet, this book has all you need to stay on track with C# 5.0. It’s widely known as the definitive reference on the language.Get up to speed on C# language basics, including syntax, types, and variablesExplore advanced topics such as unsafe code and type varianceDig deep into LINQ via three chapters dedicated to the topicLearn about code contracts, dynamic programming, and parallel programmingWork with .NET features, including reflection, assemblies, memory management, security, I/O, XML, collections, networking, and native interoperability"C# 5.0 in a Nutshell is one of the few books I keep on my desk as a quick reference." —Scott Guthrie, Microsoft"Whether you’re a novice programmer or an expert who wants to improve your knowledge of modern asynchronous programming techniques, this book has the information you need to get the job done in C#." —Eric Lippert, Microsoft

Probabilistic Robotics


Sebastian Thrun - 2005
    Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.

Introduction to Computation and Programming Using Python


John V. Guttag - 2013
    It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX.Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

How to Ace Calculus: The Streetwise Guide


Colin Conrad Adams - 1998
    Capturing the tone of students exchanging ideas among themselves, this unique guide also explains how calculus is taught, how to get the best teachers, what to study, and what is likely to be on exams—all the tricks of the trade that will make learning the material of first-semester calculus a piece of cake. Funny, irreverent, and flexible, How to Ace Calculus shows why learning calculus can be not only a mind-expanding experience but also fantastic fun.

TCP/IP Protocol Suite


Behrouz A. Forouzan - 1999
    TCP/IP Protocol Suite teaches students and professionals, with no prior knowledge of TCP/IP, everything they need to know about the subject. This comprehensive book uses hundreds of figures to make technical concepts easy to grasp, as well as many examples, which help tie the material to the real-world. The second edition of TCP/IP Protocol Suite has been fully updated to include all of the recent technology changes in the field. Many new chapters have been added such as one on Mobile IP, Multimedia and Internet, Network Security, and IP over ATM. Additionally, out-of-date material has been overhauled to reflect recent changes in technology.

Computer Networking: A Top-Down Approach


James F. Kurose - 2000
    Building on the successful top-down approach of previous editions, this fourth edition continues with an early emphasis on application-layer paradigms and application programming interfaces, encouraging a hands-on experience with protocols and networking concepts.

Machine Learning for Hackers


Drew Conway - 2012
    Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data

Haskell: The Craft of Functional Programming


Simon Thompson - 1996
    Running examples and case studies highlight new concepts and alternative approaches to program design.

Computer Organization & Design: The Hardware/Software Interface


David A. Patterson - 1993
    More importantly, this book provides a framework for thinking about computer organization and design that will enable the reader to continue the lifetime of learning necessary for staying at the forefront of this competitive discipline. --John Crawford Intel Fellow Director of Microprocessor Architecture, Intel The performance of software systems is dramatically affected by how well software designers understand the basic hardware technologies at work in a system. Similarly, hardware designers must understand the far reaching effects their design decisions have on software applications. For readers in either category, this classic introduction to the field provides a deep look into the computer. It demonstrates the relationship between the software and hardware and focuses on the foundational concepts that are the basis for current computer design. Using a distinctive learning by evolution approach the authors present each idea from its first principles, guiding readers through a series of worked examples that incrementally add more complex instructions until they ha

Mathematics for 3D Game Programming and Computer Graphics


Eric Lengyel - 2001
    Unfortunately, most programmers frequently have a limited understanding of these essential mathematics and physics concepts. MATHEMATICS AND PHYSICS FOR PROGRAMMERS, THIRD EDITION provides a simple but thorough grounding in the mathematics and physics topics that programmers require to write algorithms and programs using a non-language-specific approach. Applications and examples from game programming are included throughout, and exercises follow each chapter for additional practice. The book's companion website provides sample code illustrating the mathematical and physics topics discussed in the book.