Title: Machine Learning for Hackers: Case Studies and Algorithms to Get You Started
Publisher: O'Reilly
Publication Date: 2012
Language: English
ISBN 10: 1449303714
ISBN 13: 9781449303716
Binding: Paperback
Condition: Very Good

About this title

Synopsis

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 na�ve 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

About the Authors

Drew Conway is a PhD candidate in Politics at NYU. He studies international relations, conflict, and terrorism using the tools of mathematics, statistics, and computer science in an attempt to gain a deeper understanding of these phenomena. His academic curiosity is informed by his years as an analyst in the U.S. intelligence and defense communities.

John Myles White is a PhD candidate in Psychology at Princeton. He studies pattern recognition, decision-making, and economic behavior using behavioral methods and fMRI. He is particularly interested in anomalies of value assessment.

"About this title" may belong to another edition of this title.

Store Description

In 2002, World of Books Group was founded on an ethos to do good, protect the planet and support charities by enabling more goods to be reused. Since then, we've grown into to a global company pioneering the circular economy. Today, we drive the circular economy through three re-commerce brands: - Wob: Through Wob, we sell. We provide affordable, preloved books and media to customers all over the world. A book leaves our collection of over seven million titles and begins a new chapter every two seconds, enabling more goods to be reused. - Ziffit: Through Ziffit, we buy. We give people around the world the opportunity to contribute to the circular economy, earn money and protect the planet, by trading their unwanted books and media. - Shopiago: Through Shopiago, we help others. By sharing the technology that has grown World of Books Group into the business it is today, we?re helping charities increase revenue and reduce waste through re-commerce.

Visit Seller's Storefront

Seller's business information

World of Books Ltd
Mulberry House, Woods Way Trading Estate, Goring-By-Sea, BN12 4QY, United Kingdom

Sale & Shipping Terms

Terms of Sale

WorldofBooks.com fully embraces the AbeBooks terms and conditions and we will do
what we can to resolve any issues.

Shipping Terms

Orders ship within 2 business days. Shipping costs are based on books weighing 2.2 LB, or 1 KG. If your book order is heavy or oversized, we may contact you to let you know extra shipping is required.