Deep Learning

Columbia University - Summer 2021

Class is held online, Mon and Wed 1:10-3:40pm (2 lectures each day)

Office hours

Lecturer, Iddo Drori, Tuesday 2-4pm

CA, Kashish Chanana, Friday 8-10am

CA, Newman Cheng, Thursday 8-10pm

CA, Vaibhav Bagri, Friday 6-8pm

CA, Shantanu Jain, Thursday 8:30-10:30am

Monday, June 28 - Monday, August 16

Week 1: Foundations

Lecture 1 (Monday, June 28): Introduction

Lecture 2 (Monday, June 28): Forward and Backpropagation

Lecture 3 (Wednesday, June 30): Optimization

Lecture 4 (Wednesday, June 30): Regularization

Week 2: CNNs and RNNs

Monday, July 5, University holiday

Lecture 5 (Wednesday, July 7): Convolutional neural networks (CNNs)

Lecture 6 (Wednesday, July 7: Sequence models (RNNs, LSTM, GRU)

Week 3: GNNs and Tranformers, GANs and VAEs

Lecture 7 (Monday, July 12): Graph neural networks (GNNs)

Lecture 8 (Monday, July 12): Generative adversarial networks (GANs)

Lecture 9 (Wednesday, July 14): Transformers and chatbots

Lecture 10 (Wednesday, July 14): Variational autoencoders (VAEs)

Lecture 11 (Wednesday, July 14): Adversarial examples and probabilistic programming

Week 4: Meta Learning

Lecture 12 (Monday, July 19): Multi-task learning

Lecture 13 (Monday, July 19): Meta learning

Lecture 14 (Monday, July 19): Transfer learning

Lecture 15 (Wednesday, July 21): Automated machine learning

Lecture 16 (Wednesday, July 21): Online and continual learning

Week 5: Reinforcement Learning

Lecture 17 (Monday, July 26): Reinforcement learning

Lecture 18 (Monday, July 26): Reinforcement learning

Lecture 19 (Wednesday, July 28): Deep reinforcement learning

Lecture 20 (Wednesday, July 28): Imperfect information games

Lecture 21 (Wednesday, July 28): Math word problems

Week 6: Applications

Lecture 22 (Monday, August 2): Deep learning for self driving

Lecture 23 (Monday, August 2): Deep learning for proteomics

Lecture 24 (Monday, August 2): Deep learning for combinatorial optimization

Lecture 25 (Wednesday, August 4): Deep learning for space

Lecture 26 (Wednesday, August 4): Deep learning for program compilation, repair and synthesis

Week 7: Quantum Information Science

Lecture 27 (Monday, August 9): Quantum information science

Lecture 28 (Monday, August 9): Quantum information science

Lecture 29 (Wednesday, August 11): Quantum neural networks

Lecture 30 (Wednesday, August 11): Quantum reinforcement learning

Lecture 31 (Wednesday, August 11): Writing and reviewing best practices

Week 8: Competition Presentations

Last day of classes (Monday, August 16): FG 2021 competition

Last day of classes (Monday, August 16): Learning to learn math competition

Tutorials

Tutorial 1 (Monday, June 28): PyTorch

Tutorial 2 (Wednesday, June 30): TensorFlow

Tutorial 3 (Wednesday, July 7): Keras

Tutorial 4 (Monday, July 12): dgl.ai, GNN library

Tutorial 5 (Wednesday, July 14): huggingface.co, Transformers library

Tutorial 6 (Wednesday, July 14): pyro.ai, probabilistic programming library

Tutorial 7 (Monday, July 19): learn2learn.net, meta learning library

Tutorial 8 (Monday, July 26): RLlib, reinforcement learning library