Syllabus and Course Schedule

Time and Location: Monday, Wednesday 3:00 - 4:20pm HOA 160

EventDateDescriptionMaterials and Assignments
Lecture 1 Aug 26 Machine Learning:
Introduction to Machine Learning, Regression
Reading: Bishop: Chapter 1, Chapter 3: 3.1-3.2
Deep Learning Book: Chapters 4 and 5.
Class Notes [pdf]
Lecture 2 Aug 28 Machine Learning:
Continue Introduction to Machine Learning, Regression.
Reading: Bishop: Chapter 1, Chapter 3: 3.1-3.2
Deep Learning Book: Chapters 4 and 5.
Class Notes [pdf]
Sep 2 No class
Lecture 3 Sep 4 Probability Distributions Reading: Bishop: Chapter 2, sec. 2.1-2.4
Deep Learning Book: Chapter 3
Class Notes [pdf]
Lecture 4 Sep 9 Neural Networks I Reading: Bishop, Chapter 5: sec. 5.1 - 5.4
Deep Learning Book: Chapter 6
Class Notes [pdf]
Lecture 5 Sep 11 Neural Networks I, continue Reading: Bishop, Chapter 5: sec. 5.1 - 5.4
Deep Learning Book: Chapter 6
Class Notes [pdf]
Lecture 6 Sep 16 Neural Networks II Reading: Bishop, Bishop Chapter 5, sec. 5.1 - 5.4
Deep Learning Book: Chapter 7
Class Notes [pdf]
Lecture 7 Sep 18 Convolutional Neural Networks I Reading: Deep Learning Book: Chapter 9
Class Notes [pdf]
Lecture 8 Sep 23 Convolutional Neural Networks I, continue Reading: Deep Learning Book: Chapter 9
Class Notes [pdf]
Lecture 10 Sep 25 Convolutional Neural Networks II Reading : Deep Learning Book: Chapter 9
Class Notes [pdf]
Lecture 11 Oct 2 Graphical Models I, Midterm Review Reading : Bishop, Chapters 8.1, 8.2
Class Notes [pdf] Midterm Review [pdf]
Lecture 12 Oct 7 Graphical Models I Reading : Bishop, Chapters 8.1, 8.2
Class Notes [pdf]
Lecture 13 Oct 9 Graphical Models II Reading : Bishop, Chapters 8.3, 8.4
Class Notes [pdf]
Lecture 14 Oct 14 Autoencoders Reading : Deep Learning Book, Chapter 14
Class Notes [pdf]
Lecture 15 Oct 16 Sparse Coding Reading : Deep Learning Book, Chapter 13
Class Notes [pdf]
Lecture 16 Oct 21 Language Modeling Reading : Deep Learning Book, Chapters 10, 12.4
Class Notes [pdf]
Lecture 17 Oct 23 Sequence to Sequence Models, Part 1 Reading : Deep Learning Book, Chapter 10
Class Notes [pdf]
Lecture 18 Oct 28 Sequence to Sequence Models, Part 2 Reading : Deep Learning Book, Chapter 10
Class Notes [pdf]
Lecture 19 Oct 30 Variational Inference Reading : Deep Learning Book, Chapter 19
Class Notes [pdf]
Lecture 20 Nov 4 Variational Autoencoders Reading : Deep Learning Book, Chapter 20
Class Notes [pdf]
Lecture 21 Nov 6 Generative Adversarial Networks Reading : Deep Learning Book, Chapter 20.10
Class Notes [pdf]
Lecture 22 Nov 11 RBMs and Deep Belief Networks, part I Reading : Deep Learning Book, Chapter 20.3
Class Notes [pdf]
Lecture 23 Nov 13 Deep Belief Networks, part II Reading : Deep Learning Book, Chapter 20.3
Final review [pdf], Class Notes [pdf]
Lecture 24 Nov 18 Representation Learning for Reading Comprehension Class Notes [pdf]
Lecture 25 Nov 20 Integrating Domain-Knowledge into Deep Learning Class Notes [pdf]
Lecture 26 Nov 25 Memory for Deep Reinforcement Learning Class Notes [pdf]
Lecture 27 Dec 2 Deep Learning for Visual Navigation Class Notes [pdf]

Tentative Assigment Dates:

Check Piazza for updates:
  • Assigment 1: Out: Sep 16 -- Due: Sep 30
  • Assigment 2: Out: Oct 9 -- Due: Oct 23
  • Assigment 3: Out: Oct 30 -- Due: Nov 13

Tentative Exam Dates:

Check Piazza for updates:
  • Exam 1: Oct 8
  • Exam 2: Nov 21

Tentative Project Report Dates:

Check Piazza for updates:
  • Midway 3-page project report: Due Oct 30
  • Final 8-page project report: Due Dec 4

Books


You can also use these books for additional reference: