Recommended Resources

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:

Schedule

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