- Linear regression
- Logistic regression (classification)
- Inference
- Resampling methods
- Linear model : Selection and Regularization
- Beyong linearity (polynomials)
- Tree-based methods
- Deep Learning
- Unsupervised Learning
- Multiple Testing
I am trying to write the best of notes for Statistical Learning, I have the for reference.
It's going to be a long long task since I only take an introductory statistics courses in this semester and then I don't know when I can continue with a datascience statistics course (after Inference) but we'll see. I'll try my best to keep it updated. And yeah, the notes are 100% TEX Based though I would add some jupyter notebooks in the repository.