abdullah-alghamdi
Follow
Stars
My kaggle notebooks
Official code repo for the MARL book (www.marl-book.com)
Collection of notebooks about quantitative finance, with interactive python code.
NocoBase is an extensibility-first, open-source no-code/low-code platform for building business applications and enterprise solutions.
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
Distribute and run LLMs with a single file.
Code for "Data-Efficient Reinforcement Learning with Self-Predictive Representations"
OCR, layout analysis, reading order, table recognition in 90+ languages
A high-throughput and memory-efficient inference and serving engine for LLMs
Reinforcement Learning package for Finance
Notes and examples about Portfolio Construction and Analysis with Python (Jupyter notebooks)
Demo for the application of RL to non-stationary effects
We investigate a deep reinforcement learning (RL) architecture that supports explaining why a learned agent prefers one action over another.
Model-based reinforcement learning (generative simulator models and planning agents)
Source code for Learning Discrete State Abstractions With Deep Variational Inference. Biza, Platt, van de Meent, Wong. AABI'21. https://arxiv.org/abs/2003.04300
Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch
Datasets for data-driven deep reinforcement learning with Atari (wrapper for datasets released by Google)
A collection of reference environments for offline reinforcement learning
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
Optax is a gradient processing and optimization library for JAX.
RAD: Reinforcement Learning with Augmented Data
This project was moved to: https://github.com/coax-dev/coax
Offline Reinforcement Learning (aka Batch Reinforcement Learning) on Atari 2600 games
PyTorch implementation of AANets (CVPR 2021) and Mnemonics Training (CVPR 2020 Oral)
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.