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I'm an undergraduate student studying data science. My goal is to understand the fundamentals of this field and then move on to complex and more advanced topics. I'm interested in knowing:

  • What are some of the books I should consider reading? (from basic to advanced) which are best suited for this task?

The books should build strong fundamental knowledge about the concepts involved and should gradually take through to advanced concepts. (Multiple combination of books can be suggested as well, but the order should be preserved).

Mentioning some books I found, for your reference:

  • Data Mining: The Textbook, by Charu C. Aggarwal
  • The Elements of Statistical Learning, by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie
  • Pattern Recognition And Machine Learning, by Christopher M. Bishop
  • Machine Learning: A Probabilistic Perspective, by Kevin P. Murphy
  • Computer Age Statistical Inference: Algorithms, Evidence, and Data Science, by Bradley Efron and Trevor Hastie

Links to other answers, blogs and articles is welcomed, Thanks

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Over the years I have realized that understanding Statistics well would enable you to solve a large number of business problems and is very important too as a first step. You could take Khan Academy Probablity and Statistics Course https://www.khanacademy.org/math/statistics-probability

For Machine Learning you could read "An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani". Wonderful book. It feels almost like a novel and is beatifully written with examples and code in R.

I would also recommend Andrew NG course on Machine Learning.

For Deep Learning, I took the CS231 course by Andrew Karpathy but I liked this brilliant free online book by Micheal Nielson more. http://neuralnetworksanddeeplearning.com/

For more insight into business problems you can take up the course analytics Edge by eDX https://www.edx.org/course/the-analytics-edge

For time Series forecasting books by Rob J Hyndman are the best before you go on and solve them https://otexts.org/fpp2/

Also, I did learn a lot from blogs on Analytics Vidhya. https://www.analyticsvidhya.com/

The best way to learn is taking part in hackathons and getting hands on.

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  • $\begingroup$ Thanks for your response, I'll be sure to check those courses $\endgroup$ Nov 29, 2018 at 17:20
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I guess its common to start with "An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani" and then, if you want a deeper picture, move to "The Elements of Statistical Learning, by Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie".

I also really like the video course based on the first book, taught by Hastie and Tibshirani ( if im not mistaken) - a real gem in my mind. From my perspective its a good way to get both practical and teoretical background for machine learning. Link to the course published at R-bloggers: https://www.r-bloggers.com/in-depth-introduction-to-machine-learning-in-15-hours-of-expert-videos/

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