Data Mining: Practical Machine Learning Tools and Techniques


Ian H. Witten - 1999
    This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915            0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)

Generative Art: A Practical Guide Using Processing


Matt Pearson - 2011
    The book includes high-quality examples of generative art, along with the specific programmatic steps author and artist Matt Pearson followed to create each unique piece using the Processing programming language.About the TechnologyArtists have always explored new media, and computer-based artists are no exception. Generative art, a technique where the artist creates print or onscreen images by using computer algorithms, finds the artistic intersection of programming, computer graphics, and individual expression. The book includes a tutorial on Processing, an open source programming language and environment for people who want to create images, animations, and interactions.About the BookGenerative Art presents both the techniques and the beauty of algorithmic art. In it, you'll find dozens of high-quality examples of generative art, along with the specific steps the author followed to create each unique piece using the Processing programming language. The book includes concise tutorials for each of the technical components required to create the book's images, and it offers countless suggestions for how you can combine and reuse the various techniques to create your own works. 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. What's InsideThe principles of algorithmic artA Processing language tutorialUsing organic, pseudo-random, emergent, and fractal processes========================================​=========Table of ContentsPart 1 Creative CodingGenerative Art: In Theory and PracticeProcessing: A Programming Language for ArtistsPart 2 Randomness and NoiseThe Wrong Way to Draw A LineThe Wrong Way to Draw a CircleAdding DimensionsPart 3 ComplexityEmergenceAutonomyFractals

HTML Black Book: The Programmer's Complete HTML Reference Book


Steven Holzner - 2000
    An immediate and comprehensive answer source, rather than a diffuse tutorial, for serious programmers who want to see difficult material covered in depth without the fluff. Discusses XML, dynamic HTML, JavaScript, Java, and Perl CGI programming to create a full Web site programming package. Written by the author of several successful titles published by The Coriolis Group.

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.

Learning Spark: Lightning-Fast Big Data Analysis


Holden Karau - 2013
    How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates. Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning. Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell Leverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlib Use one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and Storm Learn how to deploy interactive, batch, and streaming applications Connect to data sources including HDFS, Hive, JSON, and S3 Master advanced topics like data partitioning and shared variables

Lean Analytics: Use Data to Build a Better Startup Faster


Alistair Croll - 2013
    Lean Analytics steers you in the right direction.This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without.Understand Lean Startup, analytics fundamentals, and the data-driven mindsetLook at six sample business models and how they map to new ventures of all sizesFind the One Metric That Matters to youLearn how to draw a line in the sand, so you’ll know it’s time to move forwardApply Lean Analytics principles to large enterprises and established products

Introduction to Computer Theory


Daniel I.A. Cohen - 1986
    Covers all the topics needed by computer scientists with a sometimes humorous approach that reviewers found refreshing. The goal of the book is to provide a firm understanding of the principles and the big picture of where computer theory fits into the field.

Doing Bayesian Data Analysis: A Tutorial Introduction with R and BUGS


John K. Kruschke - 2010
    Included are step-by-step instructions on how to carry out Bayesian data analyses.Download Link : readbux.com/download?i=0124058884            0124058884 Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan PDF by John Kruschke

A Microsoft Life


Stephen Toulouse - 2010
    Enjoy a journey through the eyes of a geek working at one of the most important companies in the world as he walks you through events both large and small. Just don't get caught in the Redmond reality distortion field! What others are saying about "A Microsoft Life": "Any self-respecting geek needs to read this book. Stepto provides an enjoyable and entertaining insight of life inside Microsoft." - Larry "Major Nelson" Hryb, Director of Programming for Xbox LIVE "Anyone who lived through the adolescent years of the computer revolution will alternate between laughing and crying (from laughing) at these great stories from inside the monolith. - Ken Denmead, NYT Bestselling Author, and editor of Geekdad.com

Ctrl+Shift+Enter Mastering Excel Array Formulas: Do the Impossible with Excel Formulas Thanks to Array Formula Magic


Mike Girvin - 2013
    Beginning with an introduction to array formulas, this manual examines topics such as how they differ from ordinary formulas, the benefits and drawbacks of their use, functions that can and cannot handle array calculations, and array constants and functions. Among the practical applications surveyed include how to extract data from tables and unique lists, how to get results that match any criteria, and how to utilize various methods for unique counts. This book contains 529 screen shots.

Bayesian Reasoning and Machine Learning


David Barber - 2012
    They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.

Statistical Rethinking: A Bayesian Course with Examples in R and Stan


Richard McElreath - 2015
    Reflecting the need for even minor programming in today's model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work.The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.Web ResourceThe book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

Digital Signal Processing: Principles, Algorithms, and Applications


John G. Proakis - 1992
    This book presents the fundamentals of discrete-time signals, systems, and modern digital processing and applications for students in electrical engineering, computer engineering, and computer science.The book is suitable for either a one-semester or a two-semester undergraduate level course in discrete systems and digital signal processing. It is also intended for use in a one-semester first-year graduate-level course in digital signal processing.

Machine Learning: The Art and Science of Algorithms That Make Sense of Data


Peter Flach - 2012
    Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

Microsoft Excel 2013 Power Programming with VBA


John Walkenbach - 2013
    Naturally, that means John Walkenbach returns with a new edition of his bestselling VBA Programming book and covers all the methods and tools you need to know in order to program with Excel. With this comprehensive guide, Mr. Spreadsheet shows you how to maximize your Excel experience using professional spreadsheet application development tips from his own personal bookshelf.Featuring a complete introduction to Visual Basic for Applications and fully updated for the latest features of Excel 2013, this essential reference includes an analysis of Excel application development and is packed with procedures, tips, and ideas for expanding Excel's capabilities with VBA.Offers an analysis of Excel application development and a complete introduction to VBA Features invaluable advice from Mr. Spreadsheet himself, bestselling author John Walkenbach, who demonstrates all the techniques you need to create Excel applications, both large and small Covers navigating the Excel interface, formatting worksheets, interacting with other Office applications, working with collaboration tools, and using sample workbooks and John Walkenbach's award-winning Power Utility Pak to help enhance your Excel skills Provides tips, tricks, and techniques for expanding Excel's capabilities with VBA that you wont find anywhere else Excel 2013 Power Programming with VBA is packed with procedures, tips, and ideas for achieving Excel excellence with VBA.