Two things I forgot to mention. If you want to see what the curriculum of a "Math for ML" from a top research uni looks like, you should check out the website

Two things I forgot to mention. If you want to see what the curriculum of a "Math for ML" from a top research uni looks like, you should check out the website of Math for ML course offered by Universitat Tubingen [0]. If you know those, you will be able to read the math of most papers that you will come across. Secondly, the best way to get started with ML is to do the Andrew Ng classic on Coursera. Then move on to FastAI [1]. Fastai is a fantastic learning resource and you will learn many nice things from Jeremy Howard that will help you make your own models. But do NOT limit yourself with fastai. It's a crappy software- too many limitation, syn sugars, API anti patterns, etc. Learn PyTorch for full-fledged projects. [0]: https://www.tml.cs.uni-tuebingen.de/teaching/2020_maths_for_ml/ https://www.tml.cs.uni-tuebingen.de/teaching/2020_maths_for_... [1]: https://fast.ai https://fast.ai