Introduction to Machine Learning

10-301 + 10-601, Fall 2019
School of Computer Science
Carnegie Mellon University

Important Notes

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

Lecture Videos

Tentative Schedule

Date Lecture Readings Announcements


Mon, 26-Aug Lecture 1 : Course Introduction
[Slides] [Video]

Wed, 28-Aug Lecture 2 : Decision Trees
[Slides] [Video]

HW1 out

Fri, 30-Aug Recitation: HW1

Mon, 2-Sep (No Class: Labor Day)

Wed, 4-Sep Lecture 3 : Decision Trees
[Slides] [Video] [Poll]

HW2 out

HW1 due

Fri, 6-Sep Recitation: HW2

Mon, 9-Sep Lecture 4 : k-Nearest Neighbors
[Slides] [Video] [Poll]

Wed, 11-Sep Lecture 5 : Model Selection
[Slides] [Video] [Poll]

Fri, 13-Sep Lecture 6 : Lecture: Perceptron
[Slides] [Video] [Poll]

Linear Models

Mon, 16-Sep Lecture 7 : Linear Regression
[Slides] [Video] [Poll]
  • Linear Regression. Kevin P. Murphy (2014). Machine Learning: A Probabilistic Perspective. Chapter 7.1-7.3.

Wed, 18-Sep Lecture 8 : Optimization for ML / Regularization
[Video] [Poll]

HW3 out

(HW2 due Thu, Sep-19)

Fri, 20-Sep Recitation: HW3

Mon, 23-Sep Lecture 9 : Stochastic Gradient Descent / Probabilistic Learning
[Slides] [Video] [Poll]

Wed, 25-Sep Lecture 10 : Midterm Exam Review / Binary Logistic Regression / Multinomial Logistic Regression
[Slides] [Video] [Poll]
  • Logistic Regression. Kevin P. Murphy (2014). Machine Learning: A Probabilistic Perspective. Chapter 1.4.6, 8.1-8.3, 8.6.

HW4 out

HW3 due

Fri, 27-Sep Recitation: Midterm Exam Review

Deep Learning

Mon, 30-Sep Lecture 11 : Feature Engineering / Neural Networks
[Slides] [Video] [Poll]

Wed, 2-Oct Lecture 12 : Neural Networks
[Slides] [Video] [Poll]

Thu, 3-Oct Midterm Exam 1 (Evening Exam) -- details will be announced on Piazza

Fri, 4-Oct Recitation: HW4

Mon, 7-Oct Lecture 13 : Backpropagation
[Slides] [Video] [Poll]

Wed, 9-Oct Lecture 14 : Deep Learning
[Slides] [Video] [Poll]
  • [Optional] Deep learning. Yann LeCun, Yoshua Bengio, & Geoffrey Hinton (2015). Nature.

Fri, 11-Oct Recitation: HW5

HW5 out

HW4 due

Learning Paradigms

Mon, 14-Oct Lecture 15 : Reinforcement Learning: Markov Decision Processes
[Slides] [Video] [Poll]

Wed, 16-Oct Lecture 16 : Reinforcement Learning: Value/Policy Iteration
[Slides] [Video] [Poll]

Recitation: Debugging

Fri, 18-Oct (No class: Mid-semester break)

Mon, 21-Oct Lecture 17 : Reinforcement Learning: Q-Learning / Deep RL
[Slides] [Video] [Poll]

Learning Theory

Wed, 23-Oct Lecture 18 : Information Theory
[Slides] [Video] [Poll]

Fri, 25-Oct (No class: Day for community engagement)

HW6 out

HW5 due

Mon, 28-Oct Lecture 19 : Information Theory
[Video] [Poll]

Generative Models

Wed, 30-Oct Lecture 20 : MLE/MAP
[Slides] [Video] [Poll]

Fri, 1-Nov Recitation: HW6

Mon, 4-Nov Lecture 21 : Midterm Exam Review / Ensemble Methods / Recommender Systems
[Slides] [Video] [Poll]

Wed, 6-Nov Lecture 22 : Bayes Framework; Bayes Classifier
[Video] [Poll]

Fri, 8-Nov Recitation: Midterm Exam Review

HW7 out

HW6 due

Graphical Models

Mon, 11-Nov Lecture 23 : Naive Bayes
[Video] [Poll]

Wed, 13-Nov Lecture 24 : Hidden Markov Models (Part I)
[Slides] [Video] [Poll]

Thu, 14-Nov Midterm Exam 2 (Evening Exam) -- 6:30pm-8:00pm

Fri, 15-Nov Recitation: HW7

Mon, 18-Nov Lecture 25 : Hidden Markov Models (Part II)
[Video] [Poll]

Learning Paradigms

Wed, 20-Nov Lecture 26 : Graphical Models (Bayes Nets and Markov Random Fields)
[Video] [Poll]

Fri, 22-Nov Lecture 27 : SVMs / Kernel Methods
[Slides] [Video] [Poll]

Mon, 25-Nov Recitation: HW8

HW8 out

HW7 due

Wed, 27-Nov (No class: Thanksgiving break)

Fri, 29-Nov (No class: Thanksgiving break)

Mon, 2-Dec Lecture 28 : Dimensionality Reduction: PCA
[Slides] [Video] [Poll]

Wed, 4-Dec Lecture 29 : Final Exam Review
[Slides] [Video] [Poll]

HW8 due

Fri, 6-Dec Recitation: Final Exam Review

Mon, Dec-09 Final Exam 8:30am-11:30am -- details will be announced on Piazza