I’m trying to learn ML. Here’s what I’m using. Correct me if I’m dumb

I am a CS undergrad (20yo). I know some ML, but I want to formalize my knowledge and actually complete a few courses that are verifiable and learn them deeply.

I don’t have any particular goal in mind. I guess the goal is to have deep knowledge about statistical learning, ML and DL so that I can be confident about what I say and use that knowledge to guide future research and projects.

I am in an undergraduate degree where basic concepts of Probability and Linear Algebra were taught, but they weren’t taught at an intuitive level, just a memorization standpoint. The external links from Cornell’s introductory ML course are really useful. I will link them below.

Here is a list of resources I’m planning to learn from, however I don’t have all the time in the world and I project I realistically have 3 months (this summer) to learn as much as I can. I need help deciding the priority order I should use and what I should focus on. I know how to code in Python.

Video/Course stuff:

Karpathy’s series: https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ (i’ve watched micrograd twice and I understand it extremely well now; I coded along side Andrej and I plan to make a YouTube video of me just talking about what I did (so that I myself can verbalise what I did to myself because the people around me are really smart and already know this); need to start makemore) Cornell CS 4/5780: https://www.cs.cornell.edu/courses/cs4780/2024sp/ Stanford’s CS229 (Andew Ng): https://www.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU CS231n (Andrej): https://cs231n.stanford.edu/ NYU DL Course (2021): https://atcold.github.io/NYU-DLSP21/

Books:

Introduction to Statistical Learning (I am reading this currently, just finished Chapter-02): https://www.statlearning.com/ d2l.ai: https://d2l.ai/ Deep Learning (Hinton): https://www.deeplearningbook.org/ Pandas: https://wesmckinney.com/book/pandas-basics https://github.com/guipsamora/pandas_exercises https://www.youtube.com/watch?v=i7v2m-ebXB4&ab_channel=KeithGalli

Intuition:

NNs: https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi Essence of Lin Alg: https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab Nice talk: https://www.youtube.com/watch?v=KJtZARuO3JY&t=2616s&ab_channel=GrantSanderson

Learn Lin Alg:

26 pages, Zico Kotler, CS229 Stanford: https://cs229.stanford.edu/section/cs229-linalg.pdf https://www.khanacademy.org/math/linear-algebra

This is all I can think of now. So, please help me.