STA5635_fa23
This is a personal repo to work on the assignments for STA5635 Applied Machine Learning at Florida State University.
Topics of each HW
| HW# | Topic | Grade I got |
|---|---|---|
| 1 | Decision Trees and Random Forest | 9/9 |
| 2 | Regression (OLS, Decision Trees, Random Forest) | 9/9 |
| 3 | Logistic Regression with Gradient Descent | 9/9 |
| 4 | TISP | 9/9 |
| 5 | FSA | 9/9 |
| 6 | LogitBoost | 9/9 |
| 7 | Neural Network | 9/9(*1) |
| 8 | Hidden Markov Model(Viterbi, Forward-Backward, Baum-Welch) | 9/9 |
| 9 | Spectral Clustering | 9/9 |
| 10 | Clustering (PCA, K-means) | 9/9(*2) |
| 11 | Principal Component Analysis | 9/9 |
| 12 | Reinforcement Learning | 9/9 |
(*1): I made a minor error calculating the loss. I should have taken the average of the losses across all the batches, but in my code, I only recorded the loss of the last batch. (*2): The grader mentioned that I need to plot contingency matrices before the relabeling. (I don't agree since the wording in the HW statement does not mention this)