There are several recommended books for this course:
Programming experience is strongly recommended for this course. Please work through the following tutorial if you do not have programming experience:
Week of | Topics | Recommended readings covering this week's lecture | Assignments due this week (posted on Canvas) |
---|---|---|---|
Jan 23 | Course Introduction | Chapter 1 of Geron book; Chapter 2 of Geron book (pg. 33-60) | |
Jan 30 | Regression, Regularization | Chapter 4 of Geron book (pg. 107-112, 123-134); Section 5.1.4 of Deep Learning Book; pg. 108-111 of Deep Learning Book; Regression Metrics (Section 3.3.4 in tutorial); (Optional Linear Algebra Background) Chapter 2 of Deep Learning Book | Problem Set 1 |
Feb 6 | Classification: Decision Tree, Naive Bayes | Chapters 3 and 6 of Geron book; Naive Bayes | Lab Assignment 1 |
Feb 13 | Classification: Nearest Neighbor, Support Vector Machine | Nearest Neighbor; Chapter 5 of Geron book | Problem Set 2 |
Feb 20 | Feature Representation, Dimensionality Reduction | Chapters 2 (pg. 60-71), 3 (pg. 89-95), and 8 of Geron book | Lab Assignment 2 |
Feb 27 | Ensemble Learning, Introduction to Computer Vision and Natural Language Processing | Chapter 7 of Geron book, Chapters 12.2 and 12.4 of Goodfellow book | Problem Set 3 |
Mar 6 | Artificial Neurons, Gradient Descent | pg. 113-123 and pg. 255-262 of Geron book, pg. 10-34 of Rashid book, pg. 1-16 of Goodfellow book | Lab Assignment 3 |
Mar 13 | Neural Network Architecture and Training | pg. 263-265 of Geron book; pg. 35-71 of Rashid book, pgs. 163-171 and pgs. 185-217 of Goodfellow book | Problem Set 4 |
Mar 20 | No Class (Spring Break) | ||
Mar 27 | Neural Network Training, Vanishing Gradients, and Optimization | Chapter 11 of Geron book (pgs. 277-306) | Lab Assignment 4 |
Apr 3 | Convolutional Neural Networks | Chapter 13 of Geron book | Project Pre-Proposal |
Apr 10 | Neural Network Regularization and Recurrent Neural Networks | Chapter 11 of Geron book (pgs. 307-315), Chapter 14 of Geron book | |
Apr 17 | Autoencoders, Unsupervised Learning (Guest: Colleen Lyon) | Chapter 15 of Geron book | Project Proposal |
Apr 24 | Bias, Ethics, and Algorithm Fairness, Accountability, and Transparency (Guest: Mehrnoosh Sameki) | Project Outline | |
May 1 | Curriculum Learning, Active Learning, Reinforcement Learning (Guest: Kim Wood) | Chapter 16 of Geron book | |
May 8 | Students' Project Presentations | Project Presentation | |
May 15 | No Class | Final Project |