Repository for all my original code project submissions for UW CSE446: Machine Learning.
| Basics |
|---|
| Basic Probability and Linear Algebra |
| Maximum Likelihood Estimation |
| Convexity |
| Irreducible Error |
| Bias-Variance Trade-off |
| Regression |
|---|
| Linear Regression + Basis Functions |
| Gradient Descent and SGD |
| Regularization |
| Sparsity and Variable Selection |
| Classification |
|---|
| Classification |
| Logistic Regression |
| Kernels |
| Neural Networks |
|---|
| Neural Network Basics |
| Backpropagation |
| Convolutional Neural Networks |
| Recurrent Neural Networks |
| Long Short-Term Memory (LSTM) |
| Attention Mechanism |
| Unsupervised Learning |
|---|
| K-means |
| Gaussian Mixture Model (GMM) |
| Principal Component Analysis (PCA) |
| Singular Value Decomposition (SVD) |
| Matrix Completion |
| Auto-encoder |