Suggest an order to read data science books

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I'm an undergraduate student that is currently studing data science. However, since we generally don't delve deeply onto things in class, I want to take some time to review the fundamentals and understand things deeply in order to advance to more complex notions. When I did some research I came across these books :

  • 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

If you know or came across these books, can you please help me choose the proper order to read these books, or tell me if these is a redundant book, or even suggest a book to add to the list

Any help is appreciated, thanks.

Ahmed Amine MAJDOUBI

Posted 2018-11-29T15:36:14.290

Reputation: 23

Question was closed 2018-12-06T04:54:11.767

Answers

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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.

Manasa Tallam

Posted 2018-11-29T15:36:14.290

Reputation: 56

Thanks for your response, I'll be sure to check those courses – Ahmed Amine MAJDOUBI – 2018-11-29T17:20:59.727

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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/

Yaroslaw Homenko

Posted 2018-11-29T15:36:14.290

Reputation: 391