Introduction to Machine Learning

10-301 + 10-601, Spring 2024
School of Computer Science
Carnegie Mellon University


Important Notes

This schedule is tentative and subject to change. Please check back often.

Tentative Schedule

Date Lecture Readings Announcements

Classification & Regression

Wed, 17-Jan Lecture 1 : Course Overview
[Slides] [Slides (Inked)]

HW1 Out

Fri, 19-Jan Recitation: HW1
[Handout] [Solutions]

Mon, 22-Jan Lecture 2 : Machine Learning as Function Approximation
[Slides] [Slides (Inked)]

Wed, 24-Jan Lecture 3 : Decision Trees
[Slides] [Slides (Inked)] [Poll]

HW1 Due

HW2 Out

Fri, 26-Jan Recitation: HW2
[Handout] [Solutions]

Mon, 29-Jan Lecture 4 : k-Nearest Neighbors
[Slides] [Slides (Inked)] [Poll]

Wed, 31-Jan Lecture 5 : Model Selection and Experimental Design
[Slides] [Slides (Inked)] [Poll]

Fri, 2-Feb (No Recitation)

Linear Models

Mon, 5-Feb Lecture 6 : Perceptron
[Slides] [Slides (Inked)] [Poll]

HW2 Due

HW3 Out

Wed, 7-Feb Lecture 7 : Linear Regression
[Slides] [Slides (Inked)] [Poll]
  • Linear Regression. Kevin P. Murphy (2014). Machine Learning: A Probabilistic Perspective. Chapter 7.1-7.3.

Fri, 9-Feb Recitation: HW3
[Handout] [Solutions]

Mon, 12-Feb Lecture 8 : Optimization for ML
[Slides] [Slides (Inked)] [Poll]

HW3 Due (only two grace/late days permitted)

Exam 1 Practice Problems out

Wed, 14-Feb Lecture 9 : Stochastic Gradient Descent / Logistic Regression
[Slides] [Slides (Inked)] [Poll]

Fri, 16-Feb Exam 1 Review OH

Mon, 19-Feb Lecture 10 : Feature Engineering / Regularization
[Slides] [Slides (Inked)] [Poll]

Mon, 19-Feb Exam 1 (evening exam, details will be announced on Piazza) 7p - 9p

HW4 Out

Neural Networks

Wed, 21-Feb Lecture 11 : Neural Networks
[Slides] [Slides (Inked)] [Poll]

Fri, 23-Feb Recitation: HW4
[Handout] [Solutions]

Mon, 26-Feb Lecture 12 : Backpropagation I
[Slides] [Slides (Inked)] [Poll]

Wed, 28-Feb Lecture 13 : Backpropagation II
[Slides] [Slides (Inked)] [Poll]

HW4 Due

HW5 Out

Fri, 1-Mar Recitation: HW5
[Handout] [Solutions]

Mon, 4-Mar (Spring Break - No Class)

Tue, 5-Mar

Wed, 6-Mar (Spring Break - No Class)

Thu, 7-Mar

Fri, 8-Mar (Spring Break - No Class)

Learning Theory

Mon, 11-Mar Lecture 14 : PAC Learning
[Slides] [Slides (Inked)] [Poll]

Societal Impacts

Wed, 13-Mar Lecture 15 : PAC Learning / Societal Impacts of ML I
[Slides] [Slides (Inked)] [Poll]

Fri, 15-Mar Recitation: HW6
[Handout] [Solutions]

Mon, 18-Mar Lecture 16 : Societal Impacts of ML II
[Slides] [Poll]

HW5 Due

HW6 Out, Exam 2 Practice Problems out

Deep Learning

Wed, 20-Mar Lecture 17 : Foundations: CNNs
[Slides] [Slides (Inked)] [Poll]
  • Deep learning. Yann LeCun, Yoshua Bengio, & Geoffrey Hinton (2015). Nature.

Fri, 22-Mar Exam 2 Review OH

Sun, 24-Mar

HW6 Due (only two grace/late days permitted)

Mon, 25-Mar Lecture 18 : Foundations: RNNs
[Slides] [Slides (Inked)] [Poll]

Wed, 27-Mar Lecture 19 : Transformers and Autodiff
[Slides] [Slides (Inked)] [Poll]

Thu, 28-Mar Exam 2 (evening exam, details will be announced on Piazza)

HW7 Out

Fri, 29-Mar Recitation: HW7
[Handout] [Solutions] [Supplemental Material]

Reinforcement Learning

Mon, 1-Apr Lecture 20 : Reinforcement Learning: MDPs
[Slides] [Slides (Inked)] [Poll]

Wed, 3-Apr Lecture 21 : Reinforcement Learning: Value/Policy Iteration
[Slides] [Slides (Inked)] [Poll]

Fri, 5-Apr Lecture 22 : Reinforcement Learning: Q-Learning / Deep RL
[Slides] [Slides (Inked)] [Poll]

Mon, 8-Apr Recitation: HW8
[Handout] [Solutions]

HW7 Due

HW8 Out

Learning Paradigms

Wed, 10-Apr Lecture 23 : Dimensionality Reduction: PCA
[Slides] [Slides (Inked)] [Poll]

Thu, 11-Apr (Spring Carnival)

Fri, 12-Apr (Spring Carnival - No Class)

Sat, 13-Apr (Spring Carnival)

Mon, 15-Apr Lecture 24 : K-Means / Ensemble Methods: Bagging
[Slides] [Poll]

Wed, 17-Apr Lecture 25 : Ensemble Methods: Boosting / Recommender Systems
[Poll]

Fri, 19-Apr Recitation: HW9
[Handout] [Solutions]

HW8 Due

HW9 Out

Mon, 22-Apr Lecture 26 : Special Topics: Pretraining, Fine-tuning, In-context Learning
[Poll]

Exam 3 Practice Problems out

Wed, 24-Apr Lecture 27 : Special Topics: Generative Models for Vision / Significance Testing for ML
[Poll]

Thu, 25-Apr

HW9 Due (only two grace/late days permitted)

Fri, 26-Apr Exam 3 Review OH

Tue, 30-Apr Exam 3 (details will be announced on Piazza) 9:30a - 11:30a