# Foundations

## Statistics

* [Interactive Course](https://www.tensortonic.com/ml-math)
* [Interactive Book](https://personal.math.ubc.ca/~tbjw/ila/)
* [Book](https://theoryandpractice.org/stats-ds-book/intro.html)
* [Lecture](https://ucsd-css2.github.io/ucsd-css2-website/lectures/01-intro.html)

## Linear Algebra

* [Coursebook by Neuromatch](https://compneuro.neuromatch.io/tutorials/W0D3_LinearAlgebra/chapter_title.html#)
* [Channel: 3Blue1Brown](https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)

## Probability Distributions

* [Code: scipy.stats](https://docs.scipy.org/doc/scipy/reference/stats.html)
* [Article: Power Laws, Pareto Distributions and Zipf's Law](https://arxiv.org/abs/cond-mat/0412004)
* [Book: astroML](https://www.astroml.org/astroML-notebooks/chapter3/astroml_chapter3_Descriptive_Statistics.html)

## Analytical Methods

* [Code: Wolfram Alpha](https://www.wolframalpha.com/examples/mathematics)
* [Code: sympy](https://www.sympy.org/en/index.html)

## Bayesian vs Frequentist Statistics

* [Blog](https://jakevdp.github.io/blog/2014/03/11/frequentism-and-bayesianism-a-practical-intro/)