A list of important resources in my research on the portfolio management problem.
- DeepMind x UCL | RL Lecture Series 2021
- DeepMind x UCL | Deep Learning Lecture Series 2020
- Coursera | Reinforcement Learning Specialization
- FastAI | Practical Deep Learning for Coders
- Hugging Face | Deep Reinforcement Learning Course
- MIT | 6.S191
- Stanford | CS229
- Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto
- Deep Learning for Coders with fastai and PyTorch
- Vector Calculus, Susan Jane Colley (optional)
- Introduction to Probability, Bertsekas & Tsitsiklis (optional)
- Hands on Machine Learning with Scikit Learn and Tensorflow, Aurelien Geron (optional)
- Deep Learning, Ian Goodfellow and Yoshua Bengio and Aaron Courville (optional)
- An Introduction to Deep Reinforcement Learning
- Proximal Policy Optimization Algorithms
- Approximately Optimal Approximate Reinforcement Learning
- Policy Gradient Methods for Reinforcement Learning with Function Approximation
- Deterministic Policy Gradient Algorithms
- Portfolio Selection, Harry Markowitz
- A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem