Principles of Machine Learning
Boston University - Fall 2023
Course staff and office hours
Instructor: Prof. Iddo Drori, Tuesday 2-3pm, CCDS 839
Teaching Fellow: Adrish Dey, Monday 3-4pm, CCDS 825
Teaching Fellow: Hao Yu, Wednesday 3-4pm, CCDS 822
Grader: Baicheng Fang
Grader: Ye Tian
Grader: Jeya Varhini
Textbooks
Enrolled students receive a free online version
First Day of Classes (Tuesday, September 5)
Lecture 1 (Tuesday, September 5): Introduction
Lecture 2 (Thursday, September 7): Regression
Lecture 3 (Tuesday, September 12): Gradient descent
Lecture 4 (Thursday, September 14): Classifiers
Lecture 5 (Tuesday, September 19): Logistic regression
Lecture 6 (Thursday, September 21): Feature representation
Lecture 7 (Tuesday, September 26): Neural networks
Lecture 8 (Thursday, September 28): Neural networks
Lecture 9 (Tuesday, October 3): Convolutional neural networks
Lecture 10 (Thursday, October 5): Convolutional neural networks
Indigenous People’s Day Holiday (Monday, October 9) No classes
Lecture 11 (Tuesday, October 10: Sequence models
Lecture 12 (Thursday, October 12): Sequence models
Lecture 13 (Tuesday, October 17): Recurrent neural netowrks
Lecture 14 (Thursday, October 19): Recurrent neural networks
Lecture 15 (Tuesday, October 24): Attention
Lecture 16 (Thursday, October 26): Transformers
Lecture 17 (Tuesday, October 31): Markov decision processes
Lecture 18 (Thursday, November 2): Reinforcement learning
Lecture 19 (Tuesday, November 7): Reinforcement learning
Lecture 20 (Thursday, November 9): Clustering
Lecture 21 (Tuesday, November 14): Latent representations
Lecture 22 (Thursday, November 16): Decision trees
Lecture 23 (Tuesday, Novmeber 21): Presentations
Thanksgiving Recess (Wednesday, November 22 - Sunday, November 26)
Lecture 24 (Tuesday, November 28):
Lecture 25 (Thursday, November 30):
Lecture 26 (Tuesday, December 5):
Lecture 27 (Thursday, December 7):
Lecture 28 (Tuesday, December 12):
Last Day of Classes (Wednesday, December 12)