Stars
📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
A collection of (mostly) technical things every software developer should know about
Code that'll help you kickstart a personal website that showcases your work as a software developer.
💯 Curated coding interview preparation materials for busy software engineers
Rainbow: Combining Improvements in Deep Reinforcement Learning
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
A gym interface for AI safety gridworlds created in pycolab.
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code
A gallery for reinforcement learning, including frameworks, tutorials, papers, implementations, applications, etc.
Experiment code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"
Latex code for making neural networks diagrams
Coding interview questions and solutions
Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.
Catalyst.RL: A Distributed Framework for Reproducible RL Research
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
hari-sikchi / gym-gazebo
Forked from erlerobot/gym-gazeboA toolkit for developing and comparing reinforcement learning algorithms using ROS and Gazebo.
🤖 Machine Learning Summer School deadlines
A minimalist environment for decision-making in autonomous driving
A collection of reading material for the Workshop on "Structure & Priors in Reinforcement Learning" (SPiRL) at ICLR 2019.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Reinforcement learning baseline agent trained with the Actor-critic (A3C) algorithm.
A collection of multi-agent reinforcement learning OpenAI gym environments
Computational framework for reinforcement learning in traffic control
Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes
Simple and easily configurable grid world environments for reinforcement learning
Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course
Simple RNN, LSTM and Differentiable Neural Computer in pure Numpy