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Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.
In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science.
Topics include:
Statistical inference, exploratory data analysis, and the data science processAlgorithmsSpam filters, Naive Bayes, and data wranglingLogistic regressionFinancial modelingRecommendation engines and causalityData visualizationSocial networks and data journalismData engineering, MapReduce, Pregel, and Hadoop
Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.
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Publisher : O’Reilly Media; 1st edition (December 3, 2013)
Language : English
Paperback : 405 pages
ISBN-10 : 1449358659
ISBN-13 : 978-1449358655
Item Weight : 1.23 pounds
Dimensions : 6 x 0.78 x 9 inches
Customers say
Customers find the introduction in the book very informative and practical. Opinions are mixed on the writing style, with some finding it superb and easy to read, while others say it’s poorly written and rambling.
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