| 1 |
Lecture 1: Introduction |
Resource 1: Set up |
No assignment |
| 2 |
Lecture 2: Virtual Environments, Virtual Machines, and Containers |
Reading Discussion 1 |
R:EX1 |
| 3 |
Lecture 3: Kubernetes |
Reading Discussion 2 |
R:EX2 - D:EX1 |
| 4 |
Lecture 4: Dask |
Reading Discussion 3 |
R:EX3 - D:EX2 |
| 5 |
Practicum 1 |
Practicum 1 |
No assignment |
| 6 |
Lecture 5: Intro to Transfer Learning: Basic Transfer Learning and SOTA Models |
Reading Discussion 4 |
R:EX4 - D:EX3 |
| 7 |
Lecture 6: Transfer Learning 2 |
Reading Discussion 5 |
R:EX5 - D:EX4 |
| 8 |
Lecture 7: Distillation and Compression |
Reading Discussion 6 |
R:EX6 - D:EX5 |
| 9 |
Practicum 2 |
Practicum 2 |
No assignment |
| 10 |
Lecture 8: Introduction and overview of Viz for Deep Models |
Reading Discussion 7 |
R:EX7 - D:EX6 |
| 11 |
Lecture 9: Convolutional Neural Networks for Image Data |
Reading Discussion 8 |
R:EX8 - D:EX7 |
| 12 |
Lecture 10: Recurrent Neural Networks for Text Data |
Reading Discussion 9 |
R:EX9 - D:EX8 |
| 13 |
Practicum 3 |
Practicum 3 |
No assignment |
| 14 |
Project |
Project |
No assignment |
| 15 |
Project |
Project |
No assignment |