NTU Machine Learning (EE5184, Spring 2022)
Instructor: Prof. Hong-yi Lee
Website: ML2022 Spring
Github: Github
| # | Topic | Task | Public Score | Private Score | Score | Ranking |
|---|---|---|---|---|---|---|
| 1 | Regression | COVID-19 Cases Prediction | 0.83911 | 0.90092 | 9 | 154/944 Top 16% |
| 2 | Classification | MFCC Classification | 0.84441 | 0.84562 | 10 | 13/615 Top 2% |
| 3 | Convolutional Neural Network | Food-11 Classification | 0.92131 | 0.89159 | 10 | 43/549 Top 8% |
| 4 | Self-Attention | Speaker Identification | 0.86850 | 0.86575 | 10 | 41/517 Top 8% |
| 5 | Transformer | English to Traditional Chinese Machine Translation | 36.29 | 36.32 | 10 | 3/389 Top 1% |
| 6 | Generative Adversarial Network | Anime Face Generation | 0.812(AFD) 8395.97(FID) |
NA | 10 | 16/433 Top 4% |
| 7 | BERT | Extractive Question Answering | 0.85195 | 0.84019 | 10 | 6/491 Top 1% |
| 8 | AutoEncoder | Human Faces Anomaly Detection | 0.83170 | 0.83517 | 10 | 15/495 Top 3% |
| 9 | Explainable AI | CNN & BERT Explanation | NA | NA | 9.6 | NA |
| 10 | Adversarial Attack | Black-Box Attack | 0.11 | NA | 10 | 89/428 Top 21% |
| 11 | Domain Adaptation | Adaptation from real to drawing image | 0.82774 | 0.82478 | 10 | 36/372 Top 10% |
| 12 | Reinforcement Learning | Lunar Lander | 286 | NA | 10 | 20/301 Top 7% |
| 13 | Network Compression | Food-11 Classification | 0.85956 | 0.84421 | 9.75 | 16/257 Top 6% |
| 14 | Life Long Learning | Rotated MNIST Classification | NA | NA | 10 | NA |
| 15 | Meta Learning | Few-shot Classification | 0.95187 | 0.95562 | 10 | 61/194 Top 31% |
OS: Ubuntu 20.04.3 LTS (Focal Fossa)
Language: Python 3.8.10
NVIDIA Driver: 470.74
CUDA Version: CUDA 11.1