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

Classification

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
[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

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
[Video] [Poll]

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

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

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

Learning Theory

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

Fri, 1-Nov Recitation: HW6

Mon, 4-Nov Lecture 21 : Dimensionality Reduction: PCA
[Video] [Poll]

Wed, 6-Nov Lecture 22 : Naive Bayes / Midterm Exam Review
[Video] [Poll]

Fri, 8-Nov Recitation: Midterm Exam Review

HW7 out

HW6 due

Learning Paradigms

Mon, 11-Nov Lecture 23 : K-Means / Clustering
[Video] [Poll]

Wed, 13-Nov Lecture 24 : SVMs / Kernel Methods
[Video] [Poll]

Thu, 14-Nov Midterm Exam 2 (Evening Exam) -- details will be announced on Piazza

Fri, 15-Nov Recitation: HW7

Graphical Models

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

Wed, 20-Nov Lecture 26 : Hidden Markov Models (Part II)
[Video] [Poll]

HW8 out

HW7 due

Fri, 22-Nov Recitation: HW8

Mon, 25-Nov Lecture 27 : Bayesian Networks
[Video] [Poll]

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

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

Learning Paradigms

Mon, 2-Dec Lecture 28 : Ensemble Methods / Recommender Systems
[Video] [Poll]

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

Fri, 6-Dec Recitation: Final Exam Review

HW8 due

Dec 09 - 15 Final Exam Period