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.

    Scientists have marveled at the beauty and elegance of his analysis, while ordinary programmers have successfully applied his "cookbook" solutions to their day-to-day problems. All have admired Knuth for the breadth, clarity, accuracy, and good humor found in his books. "I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up.""--"Charles Long Primarily written as a reference, some people have nevertheless found it possible and interesting to read each volume from beginning to end. A programmer in China even compared the experience to reading a poem. "If you think you're a really good programmer... read Knuth's] "Art of Computer Programming.".. You should definitely send me a resume if you can read the whole thing.""--"Bill Gates Whatever your background, if you need to do any serious computer programming, you will find your own good reason to make each volume in this series a readily accessible part of your scholarly or professional library. "It's always a pleasure when a problem is hard enough that you have to get the Knuths off the shelf. I find that merely opening one has a very useful terrorizing effect on computers.""--"Jonathan LaventholIn describing the new fourth volume, one reviewer listed the qualities that distinguish all of Knuth's work. In sum: ] "detailed coverage of the basics, illustrated with well-chosen examples; occasional forays into more esoteric topics and problems at the frontiers of research; impeccable writing peppered with occasional bits of humor; extensive collections of exercises, all with solutions or helpful hints; a careful attention to history; implementations of many of the algorithms in his classic step-by-step form."--Frank RuskeyThese four books comprise what easily could be the most important set of information on any serious programmer's bookshelf.

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    A CD-ROM with demos, code, compiler, executables, and MATLAB examples has been added to the book. Simplicity and an easy narration style are the hallmarks of the book, which have made its previous seven editions immensely successful. Today s C programmer (still the language of choice in science, engineering, game programming and for handheld devices) has to master the complexities of the language and contend with its usage in environments like Windows, Linux, and for the Internet. This book covers these three aspects of C programming and doesn t assume any programming background. It begins with the basics and steadily builds the pace, so the reader finds it easy to handle more complicated topics later. This popular author has crafted hundreds of excellent programming examples and exercises for every aspect of C programming. ++++Features +Self-study format provides hundreds of step by step examples and exercises + Assumes no programming knowledge; starts with the basics and progresses to more difficult topics +Includes a CD-ROM with demos, code, compiler, executables, and MATLAB examples +Covers the latest programming techniques for Windows, Linux, and the Internet ++++++Selected Topics Traditional C Programming; Pointers; Complete Build Process; Low-level File I/O; Structures, Unions, Bit-fields; Bitwise Operators. C Under Linux; Signals and Signal Handling; Blocking of Signals; Event Driven Programming; Process; PIDs; Zombies; GNOME Programming Using GTK Library. C Under Windows. Windows Programming Model; Windows Messaging Architecture; Mouse Programming; GDI. Internet Programming. CP/ IP model; Windsock Library; Building Time Clients; Whois and HTTP Clients; Sending & Receiving emails

    The book assumes no prior knowledge of computer programming and progressively covers all the essential steps needed to become confident and proficient in using R within a day. Topics include how to input, manipulate, format, iterate (loop), query, perform basic statistics on, and plot data, via a step-by-step technique and demonstrations using in-built datasets which the reader is encouraged to replicate on their computer. Each chapter also includes exercises (with solutions) to practice key skills and empower the reader to build on the essentials gained during this introductory course.

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    You'll also receive updates when significant changes are made, as well as the final ebook version. Embedded Android is for Developers wanting to create embedded systems based on Android and for those wanting to port Android to new hardware, or creating a custom development environment. Hackers and moders will also find this an indispensible guide to how Android works.

    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.

    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.

    Introducing students to the many facets of neural networks, this text provides many case studies to illustrate their real-life, practical applications.

    A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.

    Wouldn't it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full-color book, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships.Presents a unique approach to visualizing and telling stories with data, from a data visualization expert and the creator of flowingdata.com, Nathan Yau Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design to find meaning in the numbers Details tools that can be used to visualize data-native graphics for the Web, such as ActionScript, Flash libraries, PHP, and JavaScript and tools to design graphics for print, such as R and Illustrator Contains numerous examples and descriptions of patterns and outliers and explains how to show them Visualize This demonstrates how to explain data visually so that you can present your information in a way that is easy to understand and appealing.

    You'd like to learn how to do more work with SQL inside the database before pushing data across the network to your applications. You'd like to take your SQL skills to the next level.Let's face it, SQL is a deceptively simple language to learn, and many database developers never go far beyond the simple statement: SELECT columns FROM table WHERE conditions. But there is so much more you can do with the language. In the SQL Cookbook, experienced SQL developer Anthony Molinaro shares his favorite SQL techniques and features. You'll learn about:Window functions, arguably the most significant enhancement to SQL in the past decade. If you're not using these, you're missing outPowerful, database-specific features such as SQL Server's PIVOT and UNPIVOT operators, Oracle's MODEL clause, and PostgreSQL's very useful GENERATE_SERIES functionPivoting rows into columns, reverse-pivoting columns into rows, using pivoting to facilitate inter-row calculations, and double-pivoting a result setBucketization, and why you should never use that term in Brooklyn.How to create histograms, summarize data into buckets, perform aggregations over a moving range of values, generate running-totals and subtotals, and other advanced, data warehousing techniquesThe technique of walking a string, which allows you to use SQL to parse through the characters, words, or delimited elements of a stringWritten in O'Reilly's popular Problem/Solution/Discussion style, the SQL Cookbook is sure to please. Anthony's credo is: When it comes down to it, we all go to work, we all have bills to pay, and we all want to go home at a reasonable time and enjoy what's still available of our days. The SQL Cookbook moves quickly from problem to solution, saving you time each step of the way.

    

    In this book we analyze solutions to more than 200 real interview problems and provide valuable insights into how to ace quantitative interviews. The book covers a variety of topics that you are likely to encounter in quantitative interviews: brain teasers, calculus, linear algebra, probability, stochastic processes and stochastic calculus, finance and programming.