Stock Trading Bot Using Deep Reinforcement LearningThe neural network model has been the fulcrum of the so-called AI revolution. Although very powerful for pattern-recognition tasks, however, the model has two main drawbacks: it tends to overfit when the training dataset is small, and it is ...
TradeBot: Bandit learning for hyper-parameters optimization of high frequency trading strategy 2022, Pattern Recognition Citation Excerpt : Compared with the well-known supervised learning algorithms aiming for prediction tasks [9–11], reinforcement learning (RL) focuses more on solving control takes vi...
Trading_with_RL.ipynb - Algos to trade fake market data, inspired by Gordon Ritter paper Machine Learning for Trading. This should run in Google Colab. Typical installation procedure: Install Anaconda python data science distribution Make an environment like conda create --name tf tensorflow or ...
Tabular Q-learning Deep Q-learning DQN on Pong Summary Chapter 7. DQN Extensions The PyTorch Agent Net library Basic DQN N-step DQN Double DQN Noisy networks Prioritized replay buffer Dueling DQN Categorical DQN Combining everything Summary References Chapter 8. Stocks Trading Using RL Trading Data...
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework. - Albert-Z-Guo/Deep-Reinf
As an IT person I had used supervised and unsupervised learning before but not RL. This book has good plain english engineering descriptions of the problem and solution as well as the maths. Rather than starting with descriptions of abstract models it shows how different challenges can be physica...
Wai, H.T., Yang, Z., Wang, Z., Hong, M.: Multi-agent reinforcement learning via double averaging primal-dual optimization. In: Advances in Neural Information Processing Systems, pp. 9649–9660 (2018) Google Scholar OpenAI: Openai dota 2 1v1 bot. https://openai.com/the-international/ ...
Reinforcement learning has long been advertised as the one with the capability to intelligently mimic and understand human learning and behavior. While the
Deep Q-learning DQN on Pong Summary Chapter 7. DQN Extensions The PyTorch Agent Net library Basic DQN N-step DQN Double DQN Noisy networks Prioritized replay buffer Dueling DQN Categorical DQN Combining everything Summary References Chapter 8. Stocks Trading Using RL Trading...
DLI course:Fundamentals of Deep Learning GTC session:Training Robot Behavior at Scale in the AWS Cloud With the NVIDIA Isaac Robotics Platform GTC session:Reward Fine-Tuning for Faster and More Accurate Unsupervised Object Discovery GTC session:Applying Artificial Intelligence in Quantitative Trading ...