Implment regularized linear model regression (polynomial basis) and do visualization.
2-1: Use MNIST dataset to implment Naive Bayes classifier.
2-2: Use online learning to learn the beta distribution of the parameter p (chance to see 1) of the coin tossing trails in batch.
Implment random data generator and use the data from it to do Sequential Estimator and Baysian Linear Regression.
4-1: Implment Logistic Regression.
4-2: Use MNIST dataset to implment EM algorithm.
5-1: Implement Gaussian Process.
5-2: SVM on MNIST dataset
6-1: Kernel K-means
6-2: Spectral Clustering
7-1: Kernel Eigenfaces
7-2: t-SNE