CS498_AML

1. Classification with Naive Bayes, SVM and Decision Forest
2. Implement Support Vector Machine using Stochastic Gradient Descent
3. Principal Component Analysis and Principal Coordinate Analysis
4. Low Rank Approximations
5. Clustering and Vector Quantization (K-Means)
6. Linear Regression
7. Regularized Linear Regression and Logistic Regression
8. EM Topic Models and Image Segmentation using EM
9. Variational Inference and Mean Field Inference
10. Convolutional Neural Networks
11. Variational Autoencoders