I'm glad to see mathematics guides, social leaders, and research papers included in this list. It's one thing to google "nlp tutorial" but another to know who to follow and even where to find more advanced content.
I'm a neophyte to ML, but one course I very much enjoyed auditing was "Learning from Data" [1] taught by Caltech Professor Yaser Abu-Mostafa. I found concept of the _Learning Model_ particularly fresh representation of the ML activity (starting at 14:39 in the first video linked here [2])
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[ 4.8 ms ] story [ 46.2 ms ] threadAlso Hugo Larochelle's course is great for beginners!
http://aiweekly.co
[1]: http://work.caltech.edu/telecourse.html [2]: https://youtu.be/mbyG85GZ0PI?t=14m39s
https://sebastianraschka.com/
the author of Python Machine Learning. He's great at explaining things, wrote the bets intro to ML book IMHO and is a good Twitter follow.
I also humbly submit my own guide, from the perspective of how to approach studying it amidst all the resources available:
http://karlrosaen.com/ml/