Thanks a lot for sharing the list of books and resources.
Here are some more that are not listed.
## very easy read, but very interesting to know
http://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf
## a book I did not see
Machine Learning: a Probabilistic Perspective
http://www.cs.ubc.ca/~murphyk/MLbook/
## Dr. Michael I Jordan
https://people.eecs.berkeley.edu/~jordan/
http://mlg.eng.cam.ac.uk/mlss09/mlss_slides/Jordan_1.pdf
https://www.nap.edu/catalog/18374/frontiers-in-massive-data-analysis
## for people who are interested in finding a data related job
https://www.dezyre.com/article/100-data-science-interview-questions-and-answers-general-for-2016/184
https://www.datascienceweekly.org/pdf/DataScienceWeekly-DataScientistInterviews-Vol1-April2014.pdf ## stand on giant's shoulder
https://www.springboard.com/blog/wp-content/uploads/2016/07/UltimateGuidetoDataScienceInterviews-1.pdf
## a free deep learning book
http://www.deeplearningbook.org/
## conventional explanation of deep learning
http://blog.algorithmia.com/introduction-to-deep-learning-2016/
## by Yann LeCun, Yoshua Bengio & Geoffrey Hinton
http://www.nature.com/nature/journal/v521/n7553/full/nature14539.html
Enjoy!
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