4 ms·
Your learning sabbatical seems very well thought out and I'm glad your documenting your journey publicly so others can learn with you. I actually started down
by ponderingHplus 10y ago
Your learning sabbatical seems very well thought out and I'm glad your documenting your journey publicly so others can learn with you.
I actually started down a similar path to self-learn AI, but ended up going the conventional Masters degree route. I even setup a skeleton of a blog to document the journey.
The home page has some courses you may want to add to your resource list. I've taken quite a few courses on Udacity and have enjoyed almost all of them.
http://cole-maclean.github.io/About/ http://cole-maclean.github.io/About/
Good luck on your adventure!
- krosaen 10y agoThanks! That graphic at http://cole-maclean.github.io/ http://cole-maclean.github.io/ is pretty neat, I take it that was your WIP on your self-study before you opted for the masters program? Good luck to you as well.
- gtani 10y agoThere's lots of preparatory ML reading lists, e.g. metacademy.org roadmap, Goodfellow et al. DL book, Shalev-Shwartz/Ben-David ML text (both books freely available content), review materials on Stanford course syllabuses by Socher, Ng and Karpathy. Usual recs are Strang or Axler Linear Algebra, Ross or Tsitsiklis for Probability, Spivak Calculus, Boyd Convex Optimization, and other folks will recommend real analysis, diff eq's, topology, etc.