Book picks similar to
The Mathematica Guidebook for Programming by Michael Trott
programming
computer-science
math
mathematica
Algorithms
Sanjoy Dasgupta - 2006
Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal. Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read. Tim Roughgarden Stanford University
Introducing Windows 8.1 for It Professionals
Ed Bott - 2013
It is offered for sale in print format as a convenience.Get a head start evaluating Windows 8.1 - with early technical insights from award-winning journalist and Windows expert Ed Bott. Based on the Windows 8.1 Preview release, this guide introduces new features and capabilities, with scenario-based advice on how Windows 8.1 can meet the needs of your business. Get the high-level overview you need to begin preparing your deployment now.Preview new features and enhancements, including:How features compare to Windows 7 and Windows XP The Windows 8.1 user experience Deployment Security features Internet Explorer 11 Delivering Windows apps Recovery options Networking and remote access Managing mobile devices Virtualization Windows RT 8.1
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.
How to Solve It: Modern Heuristics
Zbigniew Michalewicz - 2004
Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.
Gödel, Escher, Bach: An Eternal Golden Braid
Douglas R. Hofstadter - 1979
However, according to Hofstadter, the formal system that underlies all mental activity transcends the system that supports it. If life can grow out of the formal chemical substrate of the cell, if consciousness can emerge out of a formal system of firing neurons, then so too will computers attain human intelligence. Gödel, Escher, Bach is a wonderful exploration of fascinating ideas at the heart of cognitive science: meaning, reduction, recursion, and much more.
Machine Learning Yearning
Andrew Ng
But building a machine learning system requires that you make practical decisions: Should you collect more training data? Should you use end-to-end deep learning? How do you deal with your training set not matching your test set? and many more. Historically, the only way to learn how to make these "strategy" decisions has been a multi-year apprenticeship in a graduate program or company. This is a book to help you quickly gain this skill, so that you can become better at building AI systems.
Algorithms Illuminated (Part 1): The Basics
Tim Roughgarden - 2017
Their applications range from network routing and computational genomics to public-key cryptography and database system implementation. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. Algorithms Illuminated is an accessible introduction to the subject---a transcript of what an expert algorithms tutor would say over a series of one-on-one lessons. The exposition is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. Part 1 of the book series covers asymptotic analysis and big-O notation, divide-and-conquer algorithms and the master method, randomized algorithms, and several famous algorithms for sorting and selection.
Rethinking the Internet of Things: A Scalable Approach to Connecting Everything
Francis Dacosta - 2013
Billions of interconnected devices will be monitoring the environment, transportation systems, factories, farms, forests, utilities, soil and weather conditions, oceans and resources Many of these sensors and actuators will be networked into autonomous sets, with much of the information being exchanged machine-to-machine directly and without human involvement. Machine-to-machine communications are typically terse. Most sensors and actuators will report or act upon small pieces of information - chirps. Burdening these devices with current network protocol stacks is inefficient, unnecessary and unduly increases their cost of ownership. This must change. The architecture of the Internet of Things will entail a widely distributed topology incorporating simpler chirp protocols towards at the edges of the network. Rethinking the Internet of Things describes reasons why we must rethink current approaches to the Internet of Things. Appropriate architectures that will coexist with existing networking protocols are described in detail. An architecture comprised of integrator functions, propagator nodes, and end devices, along with their interactions, is explored. What you'll learn Teaches the difference between the "normal" Internet and the Internet of Things, Describes a new architecture and its components in the "chirp" context. Explains the shortcomings of IP for IoT. Describes the anatomy of the IoT. Re-frames key ideas such as reliability. Describes how to build the IoT Who this book is forThought leaders, executives, architectural, standards and development leaders in the evolving IoT industry
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.
C# 4.0 in a Nutshell
Joseph Albahari - 2010
It is a book I recommend." --Scott Guthrie, Corporate Vice President, .NET Developer Platform, Microsoft Corporation
"A must-read for a concise but thorough examination of the parallel programming features in the .NET Framework 4." --Stephen Toub, Parallel Computing Platform Program Manager, Microsoft
"This wonderful book is a great reference for developers of all levels." -- Chris Burrows, C# Compiler Team, Microsoft
When you have questions about how to use C# 4.0 or the .NET CLR, this highly acclaimed bestseller has precisely the answers you need. Uniquely organized around concepts and use cases, this fourth edition includes in-depth coverage of new C# topics such as parallel programming, code contracts, dynamic programming, security, and COM interoperability. You'll also find updated information on LINQ, including examples that work with both LINQ to SQL and Entity Framework. This book has all the essential details to keep you on track with C# 4.0.
Get up to speed on C# language basics, including syntax, types, and variables Explore advanced topics such as unsafe code and preprocessor directives Learn C# 4.0 features such as dynamic binding, type parameter variance, and optional and named parameters Work with .NET 4's rich set of features for parallel programming, code contracts, and the code security model Learn .NET topics, including XML, collections, I/O and networking, memory management, reflection, attributes, security, and native interoperability
How Google Tests Software
James A. Whittaker - 2012
Legendary testing expert James Whittaker, until recently a Google testing leader, and two top Google experts reveal exactly how Google tests software, offering brand-new best practices you can use even if you're not quite Google's size...yet! Breakthrough Techniques You Can Actually Use Discover 100% practical, amazingly scalable techniques for analyzing risk and planning tests...thinking like real users...implementing exploratory, black box, white box, and acceptance testing...getting usable feedback...tracking issues...choosing and creating tools...testing "Docs & Mocks," interfaces, classes, modules, libraries, binaries, services, and infrastructure...reviewing code and refactoring...using test hooks, presubmit scripts, queues, continuous builds, and more. With these techniques, you can transform testing from a bottleneck into an accelerator-and make your whole organization more productive!
Dreaming in Code: Two Dozen Programmers, Three Years, 4,732 Bugs, and One Quest for Transcendent Software
Scott Rosenberg - 2007
Along the way, we encounter black holes, turtles, snakes, dragons, axe-sharpening, and yak-shaving—and take a guided tour through the theories and methods, both brilliant and misguided, that litter the history of software development, from the famous ‘mythical man-month’ to Extreme Programming. Not just for technophiles but for anyone captivated by the drama of invention, Dreaming in Code offers a window into both the information age and the workings of the human mind.
Computer Graphics: Principles and Practice
James D. Foley - 1990
It details programming with SRGP, a simple but powerful raster graphics package. Important algorithms in 2D and 3D graphics are detailed for easy implementation, and a thorough presentation of the mathematical principles of geometric transformations and viewing are included.
Algorithm Design
Jon Kleinberg - 2005
The book teaches a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.
An Introduction to General Systems Thinking
Gerald M. Weinberg - 1975
Used in university courses and professional seminars all over the world, the text has proven its ability to open minds and sharpen thinking.Originally published in 1975 and reprinted more than twenty times over a quarter century -- and now available for the first time from Dorset House Publishing -- the text uses clear writing and basic algebraic principles to explore new approaches to projects, products, organizations, and virtually any kind of system.Scientists, engineers, organization leaders, managers, doctors, students, and thinkers of all disciplines can use this book to dispel the mental fog that clouds problem-solving. As author Gerald M. Weinberg writes in the new preface to the Silver Anniversary Edition, "I havent changed my conviction that most people dont think nearly as well as they could had they been taught some principles of thinking.Now an award-winning author of nearly forty books spanning the entire software development life cycle, Weinberg had already acquired extensive experience as a programmer, manager, university professor, and consultant when this book was originally published.With helpful illustrations, numerous end-of-chapter exercises, and an appendix on a mathematical notation used in problem-solving, An Introduction to General Systems Thinking may be your most powerful tool in working with problems, systems, and solutions.