# Deep Learning

## Columbia University - Spring 2020

### Class is held in Mudd 1127, Mon and Wed 4:10-5:25pm

### Office hours (Monday-Friday)

#### Monday 3-4pm, CEPSR 620/Video call: Lecturer, Iddo Drori

#### Tuesday 11-12pm, TA room/Video call: Course Assistant, Chengkuan Chen

#### Wednesday 2-3pm, TA room/Video call: Course Assistant, Andrew Stirn

#### Thursday 11-12pm, TA room/Video call: Course Assistant, Shashwat Verma

#### Friday 10-11am, TA room/Video call: Course Assistant, Dhruv Chamania

**First Day of Classes (Tuesday, January 21)**

**Lecture 1 (Wednesday, January 22): Introduction**

**Lecture 2 (Monday, January 27): Forward and Backpropagation**

**Lecture 3 (Wednesday, January 29): Optimization**

**Competition (Friday, January 31 - Monday, March 16)**

**Lecture 4 (Monday, February 3): CNNs**

**Lecture 5 (Wednesday, February 5): RNNs**

**Lecture 6 (Monday, February 10): Transformers**

**Lecture 7 (Wednesday, February 12): GNNs**

**Lecture 8 (Monday, February 17): GANs**

**Lecture 9 (Wednesday, February 19): VAEs**

**Lecture 10 (Monday, February 24): Reinforcement Learning**

**Lecture 11 (Wednesday, February 26): Reinforcement Learning**

**Lecture 12 (Monday, March 2): Deep Reinforcement Learning**

**Lecture 13 (Wednesday, March 4): Deep Reinforcement Learning**

**No classes (Monday, March 9)**

**Lecture 14 (Wednesday, March 11): Deep Learning in Games**

**Spring Recess (Monday-Friday, March 16-20)**

**No classes (Monday, March 23)**

**No classes (Wednesday, March 25)**

**Lecture 15 (Monday, March 30): Deep Learning for AutoML**

**Lecture 16 (Wednesday, April 1): Deep Learning for Autonomous Driving**

**Lecture 17 (Monday, April 6): Fairness and Privacy for Deep Learning**

**Lecture 18 (Wednesday, April 8): Deep Learning for Protein Structure Prediction**

**Lecture 19 (Monday, April 13): Deep Learning for PSP and Medical Imaging**

**Lecture 20 (Wednesday, April 15): Information Theory for Deep Learning**

**Lecture 21 (Monday, April 20): Deep Learning and Quantum Computation**

**Lecture 22 (Wednesday, April 22): Deep Learning and Quantum Computation, TensorFlow Quantum**

**Lecture 23 (Monday, April 27): Semi-Supervised Deep Learning**

**Lecture 24 (Wednesday, April 29): Brain Graphs, Deep Graph Library**

**Lecture 25 (Monday, May 4): Project Presentations**

Session 1: Deep Reinforcement Learning

Session 2: Combinatorial Optimization

Session 3: Semi-Supervised Learning

Session 4: Data Dependent Priors

Session 5: GANs

Session 6: Applications: Bioinformatics, NLP, Cyber, Graphics

Session 7: Spatial-Temporal GNNs

**Last Day of Classes (Monday, May 4)**