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Last active December 12, 2023 17:29
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ML guided tour
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ML_gude.md

Step 0

  • MV Gaussian link
  • Math4ML video playlist
  • Deep Learning foundation and concept book Chapter 1-3
  • GLM theory link

Regression and Statistics

The main proofs are to be read from the following order -- Proofs are given here https://www.statlect.com/fundamentals-of-statistics/ It should be accompanied by the econometrics lecture given here and here

These can be accompanied by the following books

  • Foundations of Statistics for Data Scientists R and Python by Agresti and Kateri
  • Introductory Econometrics: A Modern Approach by Woodridge

For algorithmic treatment that talks about efficient mechanisms to optimize consult

  • Elements of statistical learning by Hestie book and python notebooks

Deep Learning

Given the two recent books are out the best is to use them iteratively. I am not gonna add the book by Murphy as I find it not to be self sufficient but rather regard it as a dictionary. Main books

  • Understanding deep learning by Prince book and notebook
  • Deep Learning foundation and concept book

Murphy's book for reference

  • Probabilistic Machine Learning: Advanced Topics book
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