Math

General

Title	Description & Context	Source
Essential Math for Data Science	Calculus, linear algebra, probability & statistics explained with code examples & visuals	Hadrien Jean
Mathematics for Machine Learning	All the math necessary for ML coverying every topic in great detail (400+ pages)	Marc Peter

For any basic probability concepts, search among StatQuest's videos.

Title	Description & Context	Source
Bayes Theorem Intuition	Understand what the formula is saying, why it's true, and when its useful to use	3Blue1Brown
Bayesian updating and probability density functions	Understand how a probability distribution updates with new data with Bayes rule	3Blue1Brown
Probability concepts explained: Bayesian inference for parameter estimation	Article explaining Bayes theorem & Bayesian inference	towards data science

For any basic statistics concepts, search among StatQuest's videos.

Title	Description & Context	Source
Ordinary Least Squares Regression	Visual explanation of ordinary least squares	setosa.io
How to interpret R-squared	What is R-square and how to interpret it	Statistics by Jim
Probability Density and Probability Mass Functions	Explanations, visuals, and code to learn about the topic	hadrienj's blog

For all basic Linear Algebra concepts, refer to 3blue1brown's Essence of linear algebra series.

Title	Description & Context	Source
Principal Component Analysis 4 Dummies: Eigenvectors, Eigenvalues and Dimension Reduction	Intuition of how PCA works	George Dallas
A friendly introduction to Principal Component Analysis	Full details on how PCA works. Part of a series with Eigenvectors, SVD, etc.	peterbloem.nl

For all basic Calculus concepts, refer to 3blue1brown's Essence of Calculus series.

Title	Description & Context	Source
The Matrix Calculus You Need For Deep Learning	No math knowledge is assumed beyond what you learned in calculus 1	explained.ai