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Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
Overview of State-of-the-art Deep Learning Based Methods for Time Series Forecasting
Reinforcement Learning examples implementation and explanation
DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN
A Python implementation of the Longstaff-Schwartz linear regression algorithm for the evaluation of call rights an American options.
An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
An environment compatible with open-AI gym for the secretary problem
A Guidance on PyTorch Coding Style Based on Kaggle Dogs vs. Cats
Source for the sample efficient tabular RL submission to the 2019 NIPS workshop on Biological and Artificial RL
Implementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51
Code for paper "Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning" by David Janz*, Jiri Hron*, Przemysław Mazur, Katja Hofmann, José Miguel Hernández-Lobato, Seba…
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
implementation of Bayesian Q Learning RL Algorithm
This is a pip package implementing Reinforcement Learning algorithms in non-stationary environments supported by the OpenAI Gym toolkit.
Bayesian RL using Deep Q-learning
Efficient Exploration through Bayesian Deep Q-Networks
The repository for freeCodeCamp's YouTube course, Algorithmic Trading in Python
Quantitative analysis, strategies and backtests
Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
Solutions of Reinforcement Learning, An Introduction
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Environment for reinforcement-learning algorithmic trading models