Introduction to Machine Learning

10-601, Spring 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 A/C
  • Panopto folder: [Andrew ID Required] 10-601 B/D
  • The above folders contains all the lecture video recordings for the specified section. To access them, you will need to log in with your Andrew ID.
  • 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

Wed, 17-Jan Lecture 1 : Course Overview
[Slides] [Video A/C] [Video B/D]

HW1 out

Mon, 22-Jan Lecture 2 : Decision Trees
[Slides] [Video A/C] [Video B/D]

Wed, 24-Jan Lecture 3 : k-Nearest Neighbors
[Slides] [Video A/C] [Video B/D]

HW2 out

Fri, 26-Jan Recitation: HW2

Mon, 29-Jan Lecture 4 : Model Selection
[Slides] [Video A/C] [Video B/D]

Wed, 31-Jan Lecture 5 : Perceptron
[Slides] [Video A/C] [Video B/D]

Fri, 2-Feb Recitation: Math Background

Linear Models

Mon, 5-Feb Lecture 6 : Linear Regression
[Slides] [Video A/C] [Video B/D]
  • Linear Regression. Kevin P. Murphy (2014). Machine Learning: A Probabilistic Perspective. Chapter 7.1-7.3.

HW2 due

Wed, 7-Feb Lecture 7 : Optimization for ML
[Slides] [Video A/C] [Video B/D]

HW3 out

Fri, 9-Feb Recitation: HW3

Mon, 12-Feb Lecture 8 : Probabilistic Learning
[Slides] [Video A/C] [Video B/D]

Wed, 14-Feb Lecture 9 : Logistic Regression
[Slides] [Video A/C] [Video B/D]
  • Logistic Regression. Kevin P. Murphy (2014). Machine Learning: A Probabilistic Perspective. Chapter 1.4.6, 8.1-8.3, 8.6.

HW3 due

Fri, 16-Feb Recitation: HW4

HW4 out

Mon, 19-Feb Lecture 10 : Regularization
[Slides] [Video A/C] [Video B/D]

Deep Learning

Wed, 21-Feb Lecture 11 : Neural Networks
[Slides] [Video A/C] [Video B/D]

Fri, 23-Feb Lecture 12 : Backpropagation (Monday's lecture moved here)
[Slides] [Video A/C] [Video B/D]

HW4 due (Sun)

Mon, 26-Feb Lecture 13 : Guest Lecture: Convolutional Neural Networks (CNNs), 12:00 - 12:50 PM only (see Piazza for details)
[Slides] [Video B/D]
  • [Optional] Deep learning. Yann LeCun, Yoshua Bengio, & Geoffrey Hinton (2015). Nature.

HW5 out

Wed, 28-Feb Lecture 14 : Backpropagation (cont.)
[Slides] [Video A/C] [Video B/D]

Fri, 2-Mar Recitation: HW5

Learning Theory

Mon, 5-Mar Lecture 15 : Learning Theory: PAC Learning
[Slides] [Video A/C] [Video B/D]

Wed, 7-Mar Lecture 16 : Learning Theory: PAC Learning / Midterm Exam Review
[Slides] [Video A/C] [Video B/D]

Fri, 9-Mar Lecture 17 : Guest Lecture: Recurrent Neural Networks (RNNs), 12:00 - 12:50 PM only (see Piazza for details)
[Slides] [Video B/D]

HW5 due (Fri)

Mon, 12-Mar (No class: Midsemester break)

Wed, 14-Mar (No class: Midsemester break)

Mon, 19-Mar Lecture 18 : Learning Theory: Structured Risk Minimization
[Slides] [Video A/C] [Video B/D]

Generative Models

Wed, 21-Mar Lecture 19 : Oracles, Sampling, Generative vs. Discriminative
[Slides] [Video A/C] [Video B/D]

Thu, 22-Mar Midterm Exam (Evening Exam) -- details will be announced on Piazza

Fri, 23-Mar (No recitation)

Mon, 26-Mar Lecture 20 : MLE and MAP
[Slides] [Video A/C] [Video B/D]

Wed, 28-Mar Lecture 21 : Naive Bayes
[Slides] [Video A/C] [Video B/D]

HW6 out

Fri, 30-Mar Recitation: HW6

Graphical Models

Mon, 2-Apr Lecture 22 : Hidden Markov Models (Part I)
[Slides] [Video A/C] [Video B/D]

Wed, 4-Apr Lecture 23 : Hidden Markov Models (Part II)
[Slides] [Video A/C] [Video B/D]

HW7 out

HW6 due

Fri, 6-Apr Recitation: HW7

Mon, 9-Apr Lecture 24 : Bayesian Networks
[Slides] [Video A/C] [Video B/D]

Learning Paradigms

Wed, 11-Apr Lecture 25 : Reinforcement Learning (Part I)
[Slides] [Video A/C] [Video B/D]

Fri, 13-Apr Lecture 26 : Reinforcement Learning (Part II)
[Slides] [Video A/C] [Video B/D]

Mon, 16-Apr Lecture 27 : Deep Reinforcement Learning
[Slides] [Video A/C] [Video B/D]

HW8 out

HW7 due

Wed, 18-Apr Lecture 28 : SVMs
[Slides] [Video A/C] [Video B/D]

Fri, 20-Apr (No Recitation: Spring Carnival)

Mon, 23-Apr Recitation: HW8

Wed, 25-Apr Lecture 29 : Kernels / K-Means
[Slides] [Video A/C] [Video B/D]

Fri, 27-Apr Lecture 30 : PCA / Boosting
[Slides] [Video A/C] [Video B/D]

HW9 out

HW8 due

Mon, 30-Apr Recitation: HW9

Wed, 2-May Lecture 31 : Final Exam Review
[Slides] [Video A/C] [Video B/D]

Fri, 4-May Recitation: Final Exam Review

HW9 due

14-May Final Exam 1:00 PM - 4:00 PM