Could you recommend libraries and books for learning data science in R and Python?

[grassit]

Hi Prof Matloff and other friends,

I am not a beginner but not much different I studied a bit (though not much) about statistics and machine learning a while ago, before switching to study about computer science (general non machine learning side). I am thinking about coming back to statistics and machine learning, or data science (a term which I don't fully understand and is popular nowadays), and start with some self study.

I was wondering if any of you could provide your opinions/recommendations about:

• What libraries in R and Python shall I learn? (I am not afraid of learning many, but I am not sure about the many choices of libraries).

• What books in R and Python would you recommend? (mainly for the pragmatic side for statistics, machine learning, or data science. Some books for programming and languages are also appreciated.)

• Which applications of statistics, machine learning or data science are popular in industry? NLP, computer vision, ...? (In academia, I guess biostatistics, bioinformatics, econometrics?)

Thanks.

[matloff]

Though I think R is better than Python for data science, there is no question that Python is the more popular language. Best to learn by doing, but if you want book recommendation, there is my book, the Art of R Programming, and I've always liked Dive into Python. As to libraries, you might try H2O, which has both R and Python interfaces, and is "industrial strength." I believe the most popular application area, by far, is marketing research.