Book picks similar to
Information, Randomness and Incompleteness: Papers on Algorithmic Information Theory (2nd Edition) by Gregory Chaitin
information-theory
ma-phy-cs
pimpin-aint-easy-but-computers-are
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R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Hadley Wickham - 2016
This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.
Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way.
You’ll learn how to:
Wrangle—transform your datasets into a form convenient for analysis
Program—learn powerful R tools for solving data problems with greater clarity and ease
Explore—examine your data, generate hypotheses, and quickly test them
Model—provide a low-dimensional summary that captures true "signals" in your dataset
Communicate—learn R Markdown for integrating prose, code, and results
Computers and Intractability: A Guide to the Theory of NP-Completeness
Michael R. Garey - 1979
Johnson. It was the first book exclusively on the theory of NP-completeness and computational intractability. The book features an appendix providing a thorough compendium of NP-complete problems (which was updated in later printings of the book). The book is now outdated in some respects as it does not cover more recent development such as the PCP theorem. It is nevertheless still in print and is regarded as a classic: in a 2006 study, the CiteSeer search engine listed the book as the most cited reference in computer science literature.
Programming Ruby: The Pragmatic Programmers' Guide
Dave Thomas - 2000
When Ruby first burst onto the scene in the Western world, the Pragmatic Programmers were there with the definitive reference manual, Programming Ruby: The Pragmatic Programmer's Guide.Now in its second edition, author Dave Thomas has expanded the famous Pickaxe book with over 200 pages of new content, covering all the improved language features of Ruby 1.8 and standard library modules. The Pickaxe contains four major sections:An acclaimed tutorial on using Ruby.The definitive reference to the language.Complete documentation on all built-in classes, modules, and methodsComplete descriptions of all 98 standard libraries.If you enjoyed the First Edition, you'll appreciate the expanded content, including enhanced coverage of installation, packaging, documenting Ruby source code, threading and synchronization, and enhancing Ruby's capabilities using C-language extensions. Programming for the World Wide Web is easy in Ruby, with new chapters on XML/RPC, SOAP, distributed Ruby, templating systems, and other web services. There's even a new chapter on unit testing.This is the definitive reference manual for Ruby, including a description of all the standard library modules, a complete reference to all built-in classes and modules (including more than 250 significant changes since the First Edition). Coverage of other features has grown tremendously, including details on how to harness the sophisticated capabilities of irb, so you can dynamically examine and experiment with your running code. Ruby is a wonderfully powerful and useful language, and whenever I'm working with it this book is at my side --Martin Fowler, Chief Scientist, ThoughtWorks
Introduction to the Theory of Computation
Michael Sipser - 1996
Sipser's candid, crystal-clear style allows students at every level to understand and enjoy this field. His innovative "proof idea" sections explain profound concepts in plain English. The new edition incorporates many improvements students and professors have suggested over the years, and offers updated, classroom-tested problem sets at the end of each chapter.
An Introduction to Systems Biology: Design Principles of Biological Circuits
Uri Alon - 2006
It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.
Introduction to Information Retrieval
Christopher D. Manning - 2008
Written from a computer science perspective by three leading experts in the field, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.
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.
Information: A Very Short Introduction
Luciano Floridi - 2010
In this Very Short Introduction, one of the world's leading authorities on the philosophy of information and on information ethics, Luciano Floridi, offers an illuminating exploration of information as it relates to both philosophy and science. He discusses the roots of the concept of information in mathematics and science, and considers the role of information in several fields, including biology. Floridi also discusses concepts such as "Infoglut" (too much information to process) and the emergence of an information society, and he addresses the nature of information as a communication process and its place as a physical phenomenon. Perhaps more important, he explores information's meaning and value, and ends by considering the broader social and ethical issues relating to information, including problems surrounding accessibility, privacy, ownership, copyright, and open source. This book helps us understand the true meaning of the concept and how it can be used to understand our world.About the Series: Combining authority with wit, accessibility, and style, Very Short Introductions offer an introduction to some of life's most interesting topics. Written by experts for the newcomer, they demonstrate the finest contemporary thinking about the central problems and issues in hundreds of key topics, from philosophy to Freud, quantum theory to Islam.
Numerical Linear Algebra
Lloyd N. Trefethen - 1997
The clarity and eloquence of the presentation make it popular with teachers and students alike. The text aims to expand the reader's view of the field and to present standard material in a novel way. All of the most important topics in the field are covered with a fresh perspective, including iterative methods for systems of equations and eigenvalue problems and the underlying principles of conditioning and stability. Presentation is in the form of 40 lectures, which each focus on one or two central ideas. The unity between topics is emphasized throughout, with no risk of getting lost in details and technicalities. The book breaks with tradition by beginning with the QR factorization - an important and fresh idea for students, and the thread that connects most of the algorithms of numerical linear algebra.
Absolute Java
Walter J. Savitch - 2003
Praised for providing an engaging balance of thoughtful examples and explanatory discussion, ?best-selling author Walter Savitch explains concepts and techniques in a straightforward style using understandable language and code enhanced by a suite of pedagogical tools.? "Absolute Java "is appropriate for both introductory and intermediate programming courses introducing Java.
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
Modern Database Management
Jeffrey A. Hoffer - 1994
Intended for professional development programs in introductory database management.
The R Book
Michael J. Crawley - 2007
The R language is recognised as one of the most powerful and flexible statistical software packages, and it enables the user to apply many statistical techniques that would be impossible without such software to help implement such large data sets.
Digital Systems: Principles and Applications
Ronald J. Tocci - 1977
KEY TOPICS For each new device or circuit, the authors describe the principle of the operation, give thorough examples, and then show its actual application. An excellent reference on modern digital systems.
REST API Design Rulebook
Mark Masse - 2011
This concise book presents a set of API design rules, drawn primarily from best practices that stick close to the Web’s REST architectural style. Along with rules for URI design and HTTP use, you’ll learn guidelines for media types and representational forms.
REST APIs are ubiquitous, but few of them follow a consistent design methodology. Using these simple rules, you will design web service APIs that adhere to recognized web standards. To assist you, author Mark Massé introduces the Web Resource Modeling Language (WRML), a conceptual framework he created for the design and implementation of REST APIs.
Learn design rules for addressing resources with URIs
Apply design principles to HTTP’s request methods and response status codes
Work with guidelines for conveying metadata through HTTP headers and media types
Get design tips to address the needs of client programs, including the special needs of browser-based JavaScript clients
Understand why REST APIs should be designed and configured, not coded