Book picks similar to
Neural Networks and Machine Learning by Christopher M. Bishop


machine-learning
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programming
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Java 2: The Complete Reference


Herbert Schildt - 2000
    This book is the most complete and up-to-date resource on Java from programming guru, Herb Schildt -- a must-have desk reference for every Java programmer.

Bumper to Bumper


Doug DeMuro - 2016
    Bumper to Bumper is newer, longer, and better, touting mostly original stories that include the time Doug crashed his brand-new Porsche company car into a tree, the real story behind the time Doug crushed a Chrysler PT Cruiser, the time Doug bribed a government official in South Africa, the time Doug got detained at the Canadian border on an automotive press trip, and the story of Doug’s relationship with automakers. Also, Doug wrote this description himself in the third person.

Copying and Pasting from Stack Overflow


Vinit Nayak - 2016
    Mastering this art will not only make you the most desired developer in the market, but it will transform the craziest deadline into "Consider it done, Sir".

OS X 10.10 Yosemite: The Ars Technica Review


John Siracusa - 2014
    Siracusa's overview, wrap-up, and critique of everything new in OS X 10.10 Yosemite.

An Introduction to Group Work Practice


Ronald W. Toseland - 1984
    Students will receive a grounding in areas that vary from treatment to organizational and community settings. This edition also includes of new case studies, practice examples and guiding principles.

Programming Collective Intelligence: Building Smart Web 2.0 Applications


Toby Segaran - 2002
    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

LongWalkers: The Return of the Nephilim


Stephen Quayle - 2008
    Worse, a secret society operating outside the law is intent on bringing the monsters back to life and restoring the creatures as rulers of mankind.Joshua and his ex-girlfriend soon find themselves pitted against vicious assassins, Russian Spetsnaz troops, and cold-blooded giants hungry for human flesh as they journey around the planet in their efforts to stop the secret society.But that’s only the start of their nightmare: Those reviving the army of giants have gained control of ancient stargates enabling an invasion of the seats of power around the globe including the Kremlin and White House. It's a massive power play that leaves the fate of the human race hanging in the balance.This fast-paced, spellbinding novel is a page-turner, with entertaining plot twists and surprises.“Adventure and mayhem, told with style!”“The characters showed personality and the book had imagination. I felt like I was watching a movie. The story line was great…. If you enjoy Stargate type movies I believe you'll like this book.”

Getting Clojure


Russ Olsen - 2018
    The vision behind Clojure is of a radically simple language framework holding together a sophisticated collection of programming features. Learning Clojure involves much more than just learning the mechanics of the language. To really get Clojure you need to understand the ideas underlying this structure of framework and features. You need this book: an accessible introduction to Clojure that focuses on the ideas behind the language as well as the practical details of writing code.

C Programming: Language: A Step by Step Beginner's Guide to Learn C Programming in 7 Days


Darrel L. Graham - 2016
    It is a great book, not just for beginning programmers, but also for computer users who would want to have an idea what is happening behind the scenes as they work with various computer programs. In this book, you are going to learn what the C programming language entails, how to write conditions, expressions, statements and even commands, for the language to perform its functions efficiently. You will learn too how to organize relevant expressions so that after compilation and execution, the computer returns useful results and not error messages. Additionally, this book details the data types that you need for the C language and how to present it as well. Simply put, this is a book for programmers, learners taking other computer courses, and other computer users who would like to be versed with the workings of the most popular computer language, C. In this book You'll learn: What Is The C Language? Setting Up Your Local Environment The C Structure and Data Type C Constants and Literals C Storage Classes Making Decisions In C The Role Of Loops In C Programming Functions in C Programming Structures and Union in C Bit Fields and Typedef Within C. C Header Files and Type Casting Benefits Of Using The C Language ...and much more!! Download your copy today! click the BUY button and download it right now!

Artificial Intelligence: A Modern Approach


Stuart Russell - 1994
    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

Mining of Massive Datasets


Anand Rajaraman - 2011
    This book focuses on practical algorithms that have been used to solve key problems in data mining and which can be used on even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering. The final chapters cover two applications: recommendation systems and Web advertising, each vital in e-commerce. Written by two authorities in database and Web technologies, this book is essential reading for students and practitioners alike.

Learning First, Technology Second: The Educator’s Guide to Designing Authentic Lessons


Liz Kolb - 2017
    It happens when proven teaching strategies intersect with technology tools, and yet it’s not uncommon for teachers to use a tool because it’s “fun” or because the developer promises it will help students learn.  Learning First, Technology Second offers teachers the professional learning they need to move from arbitrary uses of technology in their classrooms to thoughtful ways of adding value to student learning.   This book includes:  An introduction to the Triple E Framework that helps teachers engage students in time-on-task learning, enhance learning experiences beyond traditional means and extend learning opportunities to bridge classroom learning with students’ everyday lives.Effective strategies for using technology to create authentic learning experiences for their students.Case studies to guide appropriate tech integration.A lesson planning template to show teachers how to effectively frame technology choices and apply them in instruction.

Foundations of Statistical Natural Language Processing


Christopher D. Manning - 1999
    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.

An Introduction to Statistical Learning: With Applications in R


Gareth James - 2013
    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Automate the Boring Stuff with Python: Practical Programming for Total Beginners


Al Sweigart - 2014
    But what if you could have your computer do them for you?In "Automate the Boring Stuff with Python," you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand no prior programming experience required. Once you've mastered the basics of programming, you'll create Python programs that effortlessly perform useful and impressive feats of automation to: Search for text in a file or across multiple filesCreate, update, move, and rename files and foldersSearch the Web and download online contentUpdate and format data in Excel spreadsheets of any sizeSplit, merge, watermark, and encrypt PDFsSend reminder emails and text notificationsFill out online formsStep-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.Don't spend your time doing work a well-trained monkey could do. Even if you've never written a line of code, you can make your computer do the grunt work. Learn how in "Automate the Boring Stuff with Python.""