Syllabus and Course Schedule

Time and Location: Monday, Wednesday 11:50am - 1:10pm, GHC 4401 Rashid Auditorium
Class Videos: Class videos will be available Panopto


EventDateDescriptionMaterials and Assignments
Lecture 1 Jan 19
Introduction to Machine Learning, Regression
Reading: Bishop: Chapter 1, Chapter 3: 3.1-3.2
Deep Learning Book: Chapters 4 and 5.
Class Notes [Lecture 1]
Lecture 2 Jan 24
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 [Lecture 2]
Lecture 3 Jan 26 Neural Networks I Reading: Bishop, Chapter 5: sec. 5.1 - 5.4
Deep Learning Book: Chapter 6
Class Notes [Lecture 3]
Lecture 4 Jan 31 Neural Networks II Reading: Bishop, Bishop Chapter 5, sec. 5.1 - 5.4
Deep Learning Book: Chapter 7
Class Notes [Lecture 4]
Lecture 5 Feb 2 Convolutional Neural Networks I Reading: Deep Learning Book: Chapter 9
Class Notes [Lecture 5]
Lecture 6 Feb 7 Convolutional Neural Networks II
Start Graphical Models 		Reading: Deep Learning Book: Chapter 9
Class Notes [Lecture 6]
Lecture 7 Feb 9 Graphical Models: Directed Graphs Reading: Bishop, Chapter 8
Class Notes [Lecture 7]
Lecture 8 Feb 14 Graphical Models, Undirected Graphs /RBMs Reading: Bishop, Chapter 8
Class Notes [Lecture 8]
Lecture 9 Feb 16 Restricted Boltzmann Machine Reading: Reading: Deep Learning Book, Chapter 20.3
Class Notes [Lecture 9]
Lecture 10 Feb 21 Deep Belief Networks Reading: Reading: Deep Learning Book, Chapter 20.3
Class Notes [Lecture 10]
Lecture 11 Feb 23 Autoencoders Reading: Deep Learning Book, Chapter 14
Class Notes [Lecture 11]
Lecture 12 Feb 28 Guest Lecture: Graph Neural Networks Class Notes [Lecture 12]
Lecture 13 March 2 Language Modeling. Reading: Deep Learning Book, Chapters 10, 12.4
Class Notes [Lecture 13]
Lecture  March 7 Spring break
Lecture  March 9 Spring break
Lecture 14 March 14 Sequence to Sequence Models, Part 1 Reading: Deep Learning Book, Chapter 10
Class Notes [Lecture 14]
Lecture 15 March 16 Sequence to Sequence Models, Part 2 Reading: Deep Learning Book, Chapter 10
Class Notes [Lecture 15]
Lecture 16 March 21 Variational Inference Reading: Deep Learning Book, Chapter 19
Class Notes [Lecture 16]
Lecture 17 March 23 Variational Autoencoder Reading: Deep Learning Book, Chapter 20
Class Notes [Lecture 17]
Lecture 18 March 28 Markov Chain Monte Carlo Reading:
Class Notes [Lecture 18]
Lecture 19 March 30 Deep Boltzmann Machines Reading: Deep Learning Book, Chapter 20.4-20.6
Class Notes [Lecture 19]
Lecture 20 April 4 Generative Adversarial Networks
Normalizing Flows 		Reading: Deep Learning Book, Chapter 20.10
Class Notes [Lecture 20]
Lecture 21 April 6 Guest Lecture: Multi-Modal Learning Class Notes [Lecture 21]
Lecture 22 April 11 Representation Learning for Reading Comprehension Class Notes [Lecture 22]
Lecture 23 April 13 Integrating Domain-Knowledge into Deep Learning Class Notes [Lecture 23]
Lecture 24 April 18 Embodied AI: Language and Perception Class Notes [Lecture 24]
Lecture 25 April 20 Capsules Class Notes [Lecture 25]
Lecture 26 April 25 Attention Models for Video Understanding Class Notes [Lecture 26]
Lecture 27 April 27 TBD

Tentative Dates:

Check Piazza for updates:
  • Assigment 1: Out: Feb 2nd -- Due Feb 16th
  • Assigment 2: Out: Feb 16th -- Due March 2nd
  • Assigment 3-1: Out: Mar 21st -- Due April 4th
  • Assigment 3-2: Out: April 6th -- Due April 20th

Books

:
You can also use these books for additional reference: