TA Sections

Sections are hourly seminars held every week by the course assistants on various topics in deep learning. The topics are split between practice and theory, and are subject to change as the quarter progresses.

Section 1 (Week 1)

Getting Started with Your Project

Section 2 (Week 2)

Understanding Gradient Descent and Backpropagation

Section 3 (Week 3)

Implementation First Steps - Codebases, Baselines, and AWS

Section 4 (Week 4)

Xavier Initialization and Regularization

Section 5 (Week 5)

Midterm Review

Details on Piazza

Section 6 (Week 6)

TensorFlow and PyTorch

Section 7 (Week 7)

Debugging DL Projects

Section 8 (Week 8)

Advanced Evaluation Metrics

Section 9 (Week 9)

Writing Your Final Report