As a researcher and instructor, I'm looking for open-source books (or similar materials) that provide a relatively thorough overview of data science from an applied perspective. To be clear, I'm especially interested in a thorough overview that provides material suitable for a college-level course, not particular pieces or papers.


closed as off-topic by demongolem, senshin, Bill the Lizard, Sean Owen, Konstantin V. Salikhov May 14 '14 at 8:40

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    $\begingroup$ List questions are usually not suited for Stack Exchange websites since there isn't an "objective" answer or a way to measure the usefulness of an answer. Having said that, one of my recommendations would be MacKay's "Information Theory, Inference, and Learning Algorithms." $\endgroup$ – Ansari May 14 '14 at 0:38
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    $\begingroup$ This question appears to be off-topic because it is asks for a favorite resource. On other SE sites, this would immediately be closed. Since this is a new site, we still have to decide if this is a valid question here $\endgroup$ – demongolem May 14 '14 at 1:16
  • $\begingroup$ Fair enough regarding what constitutes a "valid" question, although on other SE sites this question would not be immediately closed as you've stated: e.g., 2495 votes, 1440 votes, 168 votes, and so on. There's great interest for these kinds of questions, even if this isn't deemed the right place. $\endgroup$ – statsRus May 14 '14 at 2:35
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    $\begingroup$ @statsRus: Try posting a question like that to SO, and it'll be closed; these questions exists because they have historical significance, but they are not considered good, on-topic questions for Stack Exchange sites, so please do not use them as evidence that you can ask similar questions here. $\endgroup$ – blunders May 15 '14 at 21:08

One book that's freely available is "The Elements of Statistical Learning" by Hastie, Tibshirani, and Friedman (published by Springer): see Tibshirani's website.

Another fantastic source, although it isn't a book, is Andrew Ng's Machine Learning course on Coursera. This has a much more applied-focus than the above book, and Prof. Ng does a great job of explaining the thinking behind several different machine learning algorithms/situations.


Data Science specialization from Johns Hopkins University at Coursera would be a great start. https://www.coursera.org/specialization/jhudatascience/1


There is free ebook "Introduction to Data Science" based on language


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