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Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. 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

Product Details :

Genre: Computers
Author: Toby Segaran
Publisher: "O'Reilly Media, Inc."
Release: 2007-08-16
File: 362 Pages
ISBN-13: 9780596550684

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BOOK EXCERPT:

Provides information on building Web 2.0 applications that have the capability to mine data created by Internet applications.

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Genre: Computers
Author: Toby Segaran
Publisher: "O'Reilly Media, Inc."
Release: 2007-08-16
File: 360 Pages
ISBN-13: 9780596517601

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eBook Download

BOOK EXCERPT:

This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. 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.

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Genre:
Author: James Boykin
Publisher: Createspace Independent Publishing Platform
Release: 2017-04-10
File: 422 Pages
ISBN-13: 1977889271

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Provides information on using a Java-based CI toolkit to mine information to build more effective Web sites.

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Genre: Computers
Author: Satnam Alag
Publisher: Manning Publications
Release: 2008
File: 397 Pages
ISBN-13: 1933988312

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The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and storage capabilities of advanced ICT. Social Collective Intelligence opens a number of challenges for researchers in both computer science and social sciences; at the same time it provides an innovative approach to solve challenges in diverse application domains, ranging from health to education and organization of work. The book will provide a cohesive and holistic treatment of Social Collective Intelligence, including challenges emerging in various disciplines (computer science, sociology, ethics) and opportunities for innovating in various application areas. By going through the book the reader will gauge insight and knowledge into the challenges and opportunities provided by this new, exciting, field of investigation. Benefits for scientists will be in terms of accessing a comprehensive treatment of the open research challenges in a multidisciplinary perspective. Benefits for practitioners and applied researchers will be in terms of access to novel approaches to tackle relevant problems in their field. Benefits for policy-makers and public bodies representatives will be in terms of understanding how technological advances can support them in supporting the progress of society and economy.

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Genre: Computers
Author: Daniele Miorandi
Publisher: Springer
Release: 2014-09-17
File: 276 Pages
ISBN-13: 9783319086811

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If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. 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 naïve Bayesian classifier to determine if an email is spam, based only on its text Use linear regression to predict the number of page views for the top 1,000 websites Learn optimization techniques by attempting to break a simple letter cipher Compare and contrast U.S. Senators statistically, based on their voting records Build a “whom to follow” recommendation system from Twitter data

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Genre: Computers
Author: Drew Conway
Publisher: "O'Reilly Media, Inc."
Release: 2012-02-13
File: 324 Pages
ISBN-13: 9781449330538

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This book primarily targets Python developers who want to learn and use Python's machine learning capabilities and gain valuable insights from data to develop effective solutions for business problems.

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Genre: Computers
Author: Luis Pedro Coelho
Publisher: Packt Publishing Ltd
Release: 2015-03-26
File: 326 Pages
ISBN-13: 9781784392888

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In this insightful book, you'll learn from the best data practitioners in the field just how wide-ranging -- and beautiful -- working with data can be. Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video. With Beautiful Data, you will: Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web Learn how to visualize trends in urban crime, using maps and data mashups Discover the challenges of designing a data processing system that works within the constraints of space travel Learn how crowdsourcing and transparency have combined to advance the state of drug research Understand how new data can automatically trigger alerts when it matches or overlaps pre-existing data Learn about the massive infrastructure required to create, capture, and process DNA data That's only small sample of what you'll find in Beautiful Data. For anyone who handles data, this is a truly fascinating book. Contributors include: Nathan Yau Jonathan Follett and Matt Holm J.M. Hughes Raghu Ramakrishnan, Brian Cooper, and Utkarsh Srivastava Jeff Hammerbacher Jason Dykes and Jo Wood Jeff Jonas and Lisa Sokol Jud Valeski Alon Halevy and Jayant Madhavan Aaron Koblin with Valdean Klump Michal Migurski Jeff Heer Coco Krumme Peter Norvig Matt Wood and Ben Blackburne Jean-Claude Bradley, Rajarshi Guha, Andrew Lang, Pierre Lindenbaum, Cameron Neylon, Antony Williams, and Egon Willighagen Lukas Biewald and Brendan O'Connor Hadley Wickham, Deborah Swayne, and David Poole Andrew Gelman, Jonathan P. Kastellec, and Yair Ghitza Toby Segaran

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Genre: Computers
Author: Toby Segaran
Publisher: "O'Reilly Media, Inc."
Release: 2009-07-14
File: 386 Pages
ISBN-13: 9781449379292

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With this book, the promise of the Semantic Web -- in which machines can find, share, and combine data on the Web -- is not just a technical possibility, but a practical reality Programming the Semantic Web demonstrates several ways to implement semantic web applications, using current and emerging standards and technologies. You'll learn how to incorporate existing data sources into semantically aware applications and publish rich semantic data. Each chapter walks you through a single piece of semantic technology and explains how you can use it to solve real problems. Whether you're writing a simple mashup or maintaining a high-performance enterprise solution,Programming the Semantic Web provides a standard, flexible approach for integrating and future-proofing systems and data. This book will help you: Learn how the Semantic Web allows new and unexpected uses of data to emerge Understand how semantic technologies promote data portability with a simple, abstract model for knowledge representation Become familiar with semantic standards, such as the Resource Description Framework (RDF) and the Web Ontology Language (OWL) Make use of semantic programming techniques to both enrich and simplify current web applications

Product Details :

Genre: Computers
Author: Toby Segaran
Publisher: "O'Reilly Media, Inc."
Release: 2009-07-09
File: 302 Pages
ISBN-13: 1449379176

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The book adopts a tutorial-based approach to introduce the user to Scikit-learn.If you are a programmer who wants to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this the book for you. No previous experience with machine-learning algorithms is required.

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Genre: Computers
Author: Raul Garreta
Publisher: Packt Publishing Ltd
Release: 2013-11-25
File: 100 Pages
ISBN-13: 9781783281947

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