Extensive summary of computational statistics. Lecture summaries, it consists of 5 parts:

- Inferential statistics/ Sampling

- Bias, var, mse and Monte Carlo simulations

- Resampling: Bootstrap & Permutation/ Model accuracy

- Resampling: Cross-validation

- Multivariate & high-dimensional data



It has a lot of examples that are used during the lectures. Has tables to make it clear/ to discriminate between subjects + has extra notes to explain things that were not clear. Very detailed
Machine learning lecture notes extensive
Machine learning lecture notes extensive