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Thanks! 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

by krosaen 10y ago

Thanks! 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 ago
There'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.