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Research
Let's take the last one must: "What Data Scientist must read" list. I just briefly took several results from Google, here is the list of 10 of them:- https://www.quora.com/What-is-a-list-of-books-that-every-data-scientist-should-read
- http://bigdata-madesimple.com/20-must-read-books-for-budding-data-scientists
- http://www.analyticsvidhya.com/blog/2015/06/infographic-read-books-analytics-data-science
- http://www.datasciencecentral.com/profiles/blogs/15-books-every-data-scientist-should-read
- http://www.mastersindatascience.org/blog/7-must-read-books-for-the-budding-data-scientist
- http://www.forbes.com/sites/gilpress/2015/03/31/3-recent-books-for-budding-data-scientists-and-business-executives-involved-with-big-data-analytics
- https://www.umbel.com/blog/big-data/must-read-big-data-books
- http://analyticstraining.com/2014/five-must-reads-for-data-scientists
- https://www.quora.com/What-are-the-must-reads-for-data-science-and-machine-learning
- http://www.analyticsvidhya.com/blog/2015/06/infographic-read-books-analytics-data-science
And what is this quick research good for? From this circa 80 books and list of several articles you get list of subjective chosen resources which lead practically to nowhere. Just several books repeating like famous Nate Silvers Signal and Noise and of course some R or other Cookbooks. So, what is conclusion?
Conclusion
This lists of books which someone else read leads me always to Vincent Granville's article Fake data science. And what you need to take from it? Pick any book you need for your field of expertise. And what should be your field of expertise? Choose some project, doesn't matter if your personal one, school or for instance from Kaggle.com. And follow up approaches which you need to for goal achievement, then pick book, course to support your path towards this goal. And by real work, life experience you will sooner or later become Data Scientist.
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