- Mathmatics for Machine Learning
- control versus adjust
- 3blue1brown: essence of linear algebra
- This provides a great conceptual overview and awesome visualizations, I would recommend watching these videos first, and then again after you've completed some of the other links.
- Khan Academy: least squares approximation
- A great complement to 3blue1brown, Sal walks through concrete examples of least squares approximation (which is essentially the linear algebra form of regression)
- Introduction to Statistical Learning: Chapter 3
- I've read the first three chapters in full, and the 3rd chapter on regression really opened up my understanding on how to interpret regression parameters
- Elements of Statistical Learning: Chapter 3
- A more formal mathematical understanding of linear regression, I haven't finished this yet.
- MumfordBrainStats: Regression overview
- Great series by Jeanette to understand regression in the context of brain science
- John Hopkins Data Science Track: Regression Models
- Currently going through this class, so far it's awesome!
- zstatistics: regression
- I used their 2nd video to understand degrees of freedom more intuitively
- Linear Algebra for Machine Learning
- Calculus for Machine Learning
- General Linear Model For Neuroimaging (FSL)