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

    As author Jeffrey Needham points out in this eye-opening book, big data can provide unprecedented insight into user habits, giving enterprises a huge market advantage. It will also inspire organizations to change the way they function."Disruptive Possibilities: How Big Data Changes Everything" takes you on a journey of discovery into the emerging world of big data, from its relatively simple technology to the ways it differs from cloud computing. But the big story of big data is the disruption of enterprise status quo, especially vendor-driven technology silos and budget-driven departmental silos. In the highly collaborative environment needed to make big data work, silos simply don't fit.Internet-scale computing offers incredible opportunity and a tremendous challenge--and it will soon become standard operating procedure in the enterprise. This book shows you what to expect.

     By the way, because he has this delusion that you should always put your money where your mouth is, he actually shows you the video where you can see his 17 Amazon Best Sellers. Bananas! He’s no saint, though! If you get his FREE COURSE he will try to sell you his complete, over-the-shoulder, professional Course down the line! He offers it for a crazy affordable price and he doesn’t even try to upsell you anything. This lunatic believes in transparency and providing real value. These are the worst scumbags! The craziest part is that, even if you don’t buy anything else, this book ALONE will give you EVERYTHING you need to publish your book on Amazon from A to Z! This is what I’ll teach you: - Choosing the Right Topic: The best way to earn a lot of money while having a sense of purpose! - Market Research: Learn how to get inspiration and improve your own book by looking at the right places! - Title Creation: Learn how to get readers bursting with curiosity and lining to get your book first! - Writing Your Book: The fastest way to structure your book all the way to the end! - Outsourcing: If you don't want to write it, learn how to outsource it the right way and end up with a masterpiece! - Cover Creation: Do it yourself easily and for free OR Get a professional graphic designer to do it for $5! - Description, Categories & Keywords: Learn the AIDA Formula for magic descriptions and know all the secrets to stand out! - Formatting and Publishing your Kindle EBook: I will provide you with the same skeleton file I personally use (already formatted! ) and I will show you, step-by-step, how to publish your Kindle book the right way! - Formatting and Publishing your Paperback Book: Learn how to publish the paperback version for FREE! I will teach how to get an already formatted template and show you, step-by-step, how to publish your physical book the right way! - Free Promotions and Getting Reviews: I will teach you how to set up a free promotion so you can get up to thousands of downloads and honest reviews that will make your book stand miles apart from your competitors! - Important Resources: Make your author's page &lt

    This guidebook is aimed clearly at the needs of the student, with a thorough understanding of, and provision for, the potential conceptual difficulties he or she is likely to encounter.

    Each formula is explained gently and in great detail, including a discussion of all the quanitites involved and examples that will make clear how and where to apply it. On top of that, there are plenty of illustrations that support the explanations and make the reading experience even more vivid.The book covers a wide range of diverse topics: acoustics, explosions, hurricanes, pipe flow, car traffic, gravity, satellites, roller coasters, flight, conservation laws, trigonometry, equations, inflation, loans, and many more. From the author of "Statistical Snacks" and "Business Math Basics - Practical and Simple".

    They shared both academic brilliance in math and a geeky awkwardness with women.Eduardo figured their ticket to social acceptance–and sexual success–was getting invited to join one of the university’s Final Clubs, a constellation of elite societies that had groomed generations of the most powerful men in the world and ranked on top of the inflexible hierarchy at Harvard. Mark, with less of an interest in what the campus alpha males thought of him, happened to be a computer genius of the first order.Which he used to find a more direct route to social stardom: one lonely night, Mark hacked into the university's computer system, creating a ratable database of all the female students on campus–and subsequently crashing the university's servers and nearly getting himself kicked out of school. In that moment, in his Harvard dorm room, the framework for Facebook was born.What followed–a real-life adventure filled with slick venture capitalists, stunning women, and six-foot-five-inch identical-twin Olympic rowers–makes for one of the most entertaining and compelling books of the year. Before long, Eduardo’s and Mark’s different ideas about Facebook created in their relationship faint cracks, which soon spiraled into out-and-out warfare. The collegiate exuberance that marked their collaboration fell prey to the adult world of lawyers and money. The great irony is that while Facebook succeeded by bringing people together, its very success tore two best friends apart.The Accidental Billionaires is a compulsively readable story of innocence lost–and of the unusual creation of a company that has revolutionized the way hundreds of millions of people relate to one another.Ben Mezrich, a Harvard graduate, has published ten books, including the New York Times bestseller Bringing Down the House. He is a columnist for Boston Common and a contributor for Flush magazine. Ben lives in Boston with his wife, Tonya.

    With amusing examples from film, TV, and history, learn how physics affects everything in your surroundings--without the use of mind-bending math or the need for a particle accelerator. With E=MC2, you'll learn: When forces balance: Simple answers to questions such as, "Why do balloons rise while apples fall?" The Good, the Bad, and the Impossible: Why The Good, the Bad, and the Ugly is full of absurdities. (For someone whose characters often uphold the law, Clint Eastwood certainly defies the laws of physics in this film.) AC/DC: but only AC really rocks: Alternating current (AC) is much more complicated than direct current (DC). The voltage is constantly moving between positive and negative; the current therefore flows one way, and then the other (rocking back and forth). Why do I feel this warm glow?: The theory behind how the first stars were born General Relativity and GPS: The strange result of gravity on time is well proven. Compared to the interminable time you experience while stuck in a traffic jam, time literally runs faster (because gravity is weaker) in the orbiting GPS satellites that help your GPS system get its fix. At the speed of light: A refresher on the theory of relativity and an understanding of why--a hundred years later--Einstein's physics still points the way in cutting-edge research. Yu again: In the martial arts movie Crouching Tiger, Hidden Dragon, the rebellious young heroine, Jen Yu, blocks an attacker with her hand without standing or bracing herself. All the while, she holds a cup of tea in her other hand and doesn't spill a drop. Find out why kinetic energy and scalar quantity make her move impossible. It's physics for the rest of us. So why not come along for the ride? Advance at the speed of light through the fundamental laws of physics as they were discovered, proven wrong, and revolutionized. Make this and all of the Blackboard Books(tm) a permanent fixture on your shelf, and you'll have instant access to a breadth of knowledge. Whether you need homework help or want to win that trivia game, this series is the trusted source for fun facts.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you'll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others. Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in Head First Data Analysis is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool. You'll learn how to:Determine which data sources to use for collecting information Assess data quality and distinguish signal from noise Build basic data models to illuminate patterns, and assimilate new information into the models Cope with ambiguous information Design experiments to test hypotheses and draw conclusions Use segmentation to organize your data within discrete market groups Visualize data distributions to reveal new relationships and persuade others Predict the future with sampling and probability models Clean your data to make it useful Communicate the results of your analysis to your audience Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, Head First Data Analysis uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.

    In the Mastering Emacs ebook you will learn the answers to all the concepts that take weeks, months or even years to truly learn, all in one place.“Emacs is such a hard editor to learn”But why is it so hard to learn? As it turns out, it's almost always the same handful of issues that everyone faces.If you have tried to learn Emacs you will have struggled with the same problems everyone faces, and few tutorials to see you through it.I have dedicated the first half of the book to explaining the essence of Emacs — and in doing so, how to overcome these issues:Memorizing Emacs’s keys: You will learn Emacs one key at a time, starting with the arrow keys. To feel productive in Emacs, it’s important you start on an equal footing — without too many new concepts and keys to memorize. Each chapter will introduce more keys and concepts so you can learn at your own pace. Discovering new modes and features: Emacs is a self-documenting editor, and I will teach you how to use the apropos, info, and describe system to discover new modes and features, or help you find things you forgot! Customizing Emacs: You don’t have to learn Emacs Lisp to alter a lot of Emacs’s functionality. Most changes you want to make are possible using Emacs’s Customize interface and I will show you how to use it efficiently. Understanding the terminology: Emacs is so old it predates almost every other editor and all modern user interfaces. I have an entire chapter dedicated to the unique terminology in Emacs; how it is different from other editors, and what that means to you.

    One slogan of Perl is that it makes easy things easy and hard things possible. "Intermediate Perl" is about making the leap from the easy things to the hard ones.Originally released in 2003 as "Learning Perl Objects, References, and Modules" and revised and updated for Perl 5.8, this book offers a gentle but thorough introduction to intermediate programming in Perl. Written by the authors of the best-selling "Learning Perl," it picks up where that book left off. Topics include: Packages and namespacesReferences and scopingManipulating complex data structuresObject-oriented programmingWriting and using modulesTesting Perl codeContributing to CPANFollowing the successful format of "Learning Perl," we designed each chapter in the book to be small enough to be read in just an hour or two, ending with a series of exercises to help you practice what you've learned. To use the book, you just need to be familiar with the material in "Learning Perl" and have ambition to go further.Perl is a different language to different people. It is a quick scripting tool for some, and a fully-featured object-oriented language for others. It is used for everything from performing quick global replacements on text files, to crunching huge, complex sets of scientific data that take weeks to process. Perl is what you make of it. But regardless of what you use Perl for, this book helps you do it more effectively, efficiently, and elegantly."Intermediate Perl" is about learning to use Perl as a programming language, and not just a scripting language. This is the book that turns the Perl dabbler into the Perl programmer.

    Understanding Computation explains theoretical computer science in a context you’ll recognize, helping you appreciate why these ideas matter and how they can inform your day-to-day programming.Rather than use mathematical notation or an unfamiliar academic programming language like Haskell or Lisp, this book uses Ruby in a reductionist manner to present formal semantics, automata theory, and functional programming with the lambda calculus. It’s ideal for programmers versed in modern languages, with little or no formal training in computer science.* Understand fundamental computing concepts, such as Turing completeness in languages* Discover how programs use dynamic semantics to communicate ideas to machines* Explore what a computer can do when reduced to its bare essentials* Learn how universal Turing machines led to today’s general-purpose computers* Perform complex calculations, using simple languages and cellular automata* Determine which programming language features are essential for computation* Examine how halting and self-referencing make some computing problems unsolvable* Analyze programs by using abstract interpretation and type systems

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    Children are given a well-rounded understanding of this beautiful fish: its anatomy, feeding habits and behavior. The following Sharks are featured:* The swift Black Tip Reef Shark* The dangerous Bull Shark* The resourceful Hammerhead Shark* The feared Great White Shark* The stealthy Lemon Shark* The fanged Nurse Shark* The gentle Whale Shark* The deceptive Wobbegong