Introduction to Machine Learning

10-601BD, Fall 2018
School of Computer Science
Carnegie Mellon University


Important Notes

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

Lecture Videos

  • Panopto folder: [Andrew ID Required] 10-601 B/D
  • The above folders contains all the lecture video recordings for the specified section(s). To access them, please select Sign in using "Canvas".
  • We have also included links to individual videos below -- however, we recommend checking the link above to find the latest videos.

Tentative Schedule

Date Lecture Readings Announcements

Classification

Mon, 27-Aug Lecture 1 : Course Overview
[Slides] [Video]

Wed, 29-Aug Lecture 2 : Decision Trees
[Slides] [Video]

HW1 out

Fri, 31-Aug Recitation: HW1
[Video]

Mon, 3-Sep No Class: Labor Day

Wed, 5-Sep Lecture 3 : Decision Trees
[Slides] [Video]

HW2 out

HW1 due

Fri, 7-Sep Recitation: HW2
[Video]

Mon, 10-Sep Lecture 4 : k-Nearest Neighbors
[Slides] [Video]

Wed, 12-Sep Lecture 5 : Model Selection
[Slides] [Video]

Fri, 14-Sep (No Recitation)

Linear Models

Mon, 17-Sep Lecture 6 : Perceptron
[Slides] [Video]

Wed, 19-Sep Lecture 7 : Linear Regression / Optimization for ML
[Slides] [Video]

HW3 out

HW2 due

Fri, 21-Sep Recitation: HW3
[Video]

Mon, 24-Sep Lecture 8 : Probabilistic Learning
[Slides] [Video]

Wed, 26-Sep Lecture 9 : Logistic Regression
[Slides] [Video]
  • Logistic Regression. Kevin P. Murphy (2014). Machine Learning: A Probabilistic Perspective. Chapter 1.4.6, 8.1-8.3, 8.6.

Fri, 28-Sep Recitation: HW4
[Video]

HW4 out (Sun)

HW3 due

Mon, 1-Oct Lecture 10 : Regularization
[Slides] [Video]

Deep Learning

Wed, 3-Oct (Lecture cancelled. Watch the short video excerpt from my Spring 2018 lecture linked below instead.)
[Video]

Fri, 5-Oct (No recitation)

Mon, 8-Oct Lecture 11 : Neural Networks (video only, see Piazza for details)
[Slides] [Video]

HW5 out (Tue)

HW4 due (Tue)

Wed, 10-Oct Lecture 12 : Backpropagation (video only, see Piazza for details)
[Slides] [Video]

Fri, 12-Oct Recitation: HW5
[Video]

Mon, 15-Oct Lecture 13 : Understanding Linear and Nonlinear Decision Boundaries
[Slides] [Video]
  • [Optional] Deep learning. Yann LeCun, Yoshua Bengio, & Geoffrey Hinton (2015). Nature.

Learning Theory

Wed, 17-Oct Lecture 14 : Learning Theory: PAC Learning
[Slides] [Video]

Fri, 19-Oct (No Recitation)

HW5 due (Sat)

Mon, 22-Oct Lecture 15 : Midterm Exam Review / Learning Theory: PAC Learning
[Slides] [Video]

Generative Models

Wed, 24-Oct Lecture 16 : Learning Theory: Structured Risk Minimization
[Slides] [Video]

Thu, 25-Oct Midterm Exam (Evening Exam, 6:30 PM - 9:30 PM) -- details will be announced on Piazza

Fri, 26-Oct (No Class: CMU Presidential Inauguration)

Mon, 29-Oct Lecture 17 : MLE and MAP
[Slides] [Video]

Wed, 31-Oct Lecture 18 : Naive Bayes
[Slides] [Video]

HW6 out

Fri, 2-Nov Recitation: HW6
[Video]

Graphical Models

Mon, 5-Nov Lecture 19 : Hidden Markov Models (Part I)
[Slides] [Video]

Wed, 7-Nov Lecture 20 : Hidden Markov Models (Part II)
[Slides] [Video]

HW7 out

HW6 due

Fri, 9-Nov Recitation: HW7
[Video]

Mon, 12-Nov Lecture 21 : Bayesian Networks
[Slides] [Video]

Learning Paradigms

Wed, 14-Nov Lecture 22 : Reinforcement Learning: Value/Policy Iteration
[Slides] [Video]

Fri, 16-Nov Lecture 23 : Reinforcement Learning: Q-Learning
[Slides] [Video]

Mon, 19-Nov Lecture 24 : Deep Reinforcement Learning
[Slides] [Video]

HW8 out

HW7 due

Wed, 21-Nov (No Class: Thanksgiving Break)

Fri, 23-Nov (No Class: Thanksgiving Break)

Mon, 26-Nov Recitation: HW8
[Video]

Wed, 28-Nov Lecture 25 : SVMs
[Slides] [Video]

Fri, 30-Nov Lecture 26 : Kernels / K-Means
[Slides] [Video]

HW9 out

HW8 due

Mon, 3-Dec Lecture 27 : PCA / Boosting
[Slides] [Video]

Wed, 5-Dec Recitation: HW9
[Video]

Fri, 7-Dec Recitation: Final Exam Review
[Slides] [Video]

HW9 due

Thu, 13-Dec Final Exam 1:00 PM - 4:00 PM