ChanBong/cs330

Overview

This repository provides notes, code and suggested readings for Deep Multi-Task and Meta Learning. These are meant to serve as a learning tool to complement the theoretical material from

• Reinforcement Learning: An Introduction (2nd Edition)
• CS 330: Deep Multi-Task and Meta Learning

Each folder in corresponds to one or more chapters of the above textbook and/or course. In addition to exercises and solution, each folder also contains a list of learning goals, a brief concept summary, notes made during class and links to the relevant readings.

All code is written in Python 3 and uses RL environments from OpenAI Gym. Advanced techniques use Pytorch for neural network implementations.

Table of Contents

• Introduction to Multi-Task and Meta Learning
• Supervised Multi-Task Learning and Transfer Learning

List of Implemented Algorithms

Resources

Textbooks

• Reinforcement Learning: An Introduction (2nd Edition)

Classes

• David Silver's Reinforcement Learning Course (UCL, 2015)
• CS 330: Deep Multi-Task and Meta Learning

Talks/Tutorials/Blogs

• Lilian Weng's blog on Meta RL

Other Projects