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.
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4$\begingroup$ 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." $\endgroup$– AnsariCommented May 14, 2014 at 0:38
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3$\begingroup$ 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 $\endgroup$– demongolemCommented May 14, 2014 at 1:16
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$\begingroup$ 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. $\endgroup$– statsRusCommented May 14, 2014 at 2:35
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1$\begingroup$ @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. $\endgroup$– blundersCommented May 15, 2014 at 21:08
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3 Answers
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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.
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2$\begingroup$ Nice one, @Nicholas... Another book from Hastie and Tibshirani is Introduction to Statistical Learning, which is a bit gentler of an entry compared to ESL. $\endgroup$ Commented May 14, 2014 at 2:16
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Data Science specialization from Johns Hopkins University at Coursera would be a great start. https://www.coursera.org/specialization/jhudatascience/1
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There is free ebook "Introduction to Data Science" based on r language
answered May 14, 2014 at 7:55