Its world-class authors provide guidance on all aspects of Bayesian data analysis and include examples of real statistical analyses, based on their own research, that demonstrate how to solve complicated problems. Changes in the new edition include:Stronger focus on MCMC Revision of the computational advice in Part III New chapters on nonlinear models and decision analysis Several additional applied examples from the authors' recent research Additional chapters on current models for Bayesian data analysis such as nonlinear models, generalized linear mixed models, and more Reorganization of chapters 6 and 7 on model checking and data collectionBayesian computation is currently at a stage where there are many reasonable ways to compute any given posterior distribution. However, the best approach is not always clear ahead of time. Reflecting this, the new edition offers a more pluralistic presentation, giving advice on performing computations from many perspectives while making clear the importance of being aware that there are different ways to implement any given iterative simulation computation. The new approach, additional examples, and updated information make Bayesian Data Analysis an excellent introductory text and a reference that working scientists will use throughout their professional life.

    

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    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

    It follows standards-based principles, but also teaches readers ways around problems they are likely to face using (X)HTML.While XHTML is the "current" standard, the book still covers HTML because many people do not yet understand that XHTML is the official successor to HTML, and many readers will still stick with HTML for backward compatibility and simpler/informal Web pages that don't require XHTML compliance.The book teaches basic principles of usability and accessibility along the way, to get users into the mode of developing Web pages that will be available to as many viewers as possible from the start. The book also covers the most commonly used programming/scripting language -- JavaScript -- and provides readers with a roadmap of other Web technologies to learn after mastering this book to add more functionality to their sites.

    This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

    Sold in over 85 countries and translated into more than 5 languages.---------------Want to get started on data science?Our promise: no math added.This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations and visuals.Popular concepts covered include:- A/B Testing- Anomaly Detection- Association Rules- Clustering- Decision Trees and Random Forests- Regression Analysis- Social Network Analysis- Neural NetworksFeatures:- Intuitive explanations and visuals- Real-world applications to illustrate each algorithm- Point summaries at the end of each chapter- Reference sheets comparing the pros and cons of algorithms- Glossary list of commonly-used termsWith this book, we hope to give you a practical understanding of data science, so that you, too, can leverage its strengths in making better decisions.

    Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. "Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk." -- Doug Cutting, Hadoop Founder, Yahoo!

    You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed.Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools.Get a straightforward synopsis of the social web landscapeUse adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+Learn how to employ easy-to-use Python tools to slice and dice the data you collectExplore social connections in microformats with the XHTML Friends NetworkApply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detectionBuild interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits"A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google

    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.

    As in the original book, Dive Into Python, each chapter starts with a real, complete code sample, proceeds to pick it apart and explain the pieces, and then puts it all back together in a summary at the end.This book includes:Example programs completely rewritten to illustrate powerful new concepts now available in Python 3: sets, iterators, generators, closures, comprehensions, and much more A detailed case study of porting a major library from Python 2 to Python 3 A comprehensive appendix of all the syntactic and semantic changes in Python 3 This is the perfect resource for you if you need to port applications to Python 3, or if you like to jump into languages fast and get going right away.

    Thus CHACHA CHAUDHARY was born in 1971.Tall and robust SABU, who is an inhabitant of planet Jupiter, gave Chaudhary an ideal company. A combination of wisdom and strength was formed to tackle any difficult task. It is said that " Chacha Chaudhary's brain works faster than a computer". Though both fight the criminals and tricksters, each episode ends with a touch of humour. The duo perform in lighter vein. The CHAUDHARY family consists of his wife Bini, a fat sharp tongue woman, Sabu, Rocket - the dog and Dag- Dag, an old truck who is half human- half machine. Chacha Chaudhary is the most popular Indian comics. More than 10 million readers enjoy this series regularly in newspapers and comic books in ten languages. A T.V. serial based on the comics has crossed 500 episodes and still continue to be telecast on premier channel "Sahara ONE".

    The classic and popular text is back with refreshed pedagogy and programming problems helps the students to have an upper hand on the practical understanding of the subject. Salient Features: Expanded discussion on Recursion (Backtracking, Simulating Recursion), Spanning Trees. Covers all important topics like Strings, Arrays, Linked Lists, Trees Highly illustrative with over 300 figures and 400 solved and unsolved exercises Content 1.Introduction and Overview 2.Preliminaries 3.String Processing 4.Arrays, Records and Pointers 5.Linked Lists 6.S tacks, Queues, Recursion 7.Trees 8.Graphs and Their Applications 9.Sorting and Searching About the Author: Seymour Lipschutz Seymour Lipschutz, Professor of Mathematics, Temple University

    Deputy Marshal in Kansas for a great deal of his life. As soon as his brother Tommy stops answering his letters, he gets extremely alarmed and decides to take matters into his own hands. When he puts a plan in place to travel to Texas, little does he know that a shattering surprise awaits him there; his brother has been found dead, next to the body of one of the most powerful ranchers in town. Will Lee manage to unravel the truth behind these enigmatic and shocking deaths?While Lee is still aghast, the local sheriff declares Tommy's death a suicide, and also accuses him of attempting robbery and murder. On the spur of the moment, the case is considered closed, which makes Lee highly suspicious. Feeling that they drag Tommy's name through the mud, he decides to defy the law and seek vindication. Will he succeed in this lonesome yet risky mission? How will he solve this demanding riddle and clear his brother's name?Lee's hazardous quest begins, having Susan Marsh and Ki'Somma, a young Cherokee medicine man, on his side. Doubts, lies, deceits, serious injuries as well as many other roadblocks will derange their endless undertaking. Will they manage to join forces triumphantly and complete this challenging mission? Or will Tommy always be remembered as a ruthless criminal?

    She is always on the trail of atrocious criminals but when her ruse is almost uncovered, her world turns upside down and she is desperate to find someone to pull her out of the fire. Luckily for her, she will partner up with Willem Stron, a lionhearted man and passing gambler who will pose as Kyle. Together they will join forces on a risky mission to guard a passing stagecoach with precious cargo. When their lives are on the line, will Willem eventually win Daisy's trust, so that they both succeed on this highly challenging undertaking?While Daisy and Willem are planning the perilous ambush, a deep affection grows for one another. Day by day, their lifetime adventure brings them closer, but they both know that if they want to stay on course, they will need to set their happily ever after aside. While struggling to focus on their quest, the sudden appearance of a wanted poster with Willem's face causes yet another series of menacing threats. How will Daisy and Willem react to this unexpected turn of events? Will they ever escape from this living nightmare and have a chance at love?When the stagecoach becomes targeted by a vicious local bandit and his gang, the two bounty hunters will deal with endless challenges that block their way. Will the legendary duo manage to protect the secretive cargo, and live to tell the tale? Or will the forces of corruption and greed overtake them at long last?A pulse-pounding drama, which will make you turn the pages with bated breath until the very last word. A must-read for fans of Western action and romance.