UC Berkeley Machine Learning 189/289A -- Study notes

---- Sept.2: 

-Inverse Covariance Matrix

Inverse Covariance Matrix:

---- Sept.3:

-Ridge Regression

Ridge Regression and PCA Regression relationship: 

Story behind Ridge Regression:

Derivation of Ridge Regression: （BU）

-Trace Matrix

-Frobenius Norm

---- Sept.4:

Properties of Matrices:

- Triangular Matrix:

---- Sept.5:

Binomial, Normal, Poisson Distribution:

- Natural number approximation

Maximum Likelihood Estimation:

- Intuition behind MLE

- Maximum A Posteriori

---- Sept.7:

- K-Folds Cross Validation

- Train/Test Split and Cross Validation in Python

- LASSO vs. Ridge Regression