Repo for the Deep Reinforcement Learning Nanodegree program
#计算机科学#NMA deep learning course
#计算机科学#The full collection of Jupyter Notebook labs from Andrew Ng's Machine Learning Specialization.
Reinforcement learning with A* and a deep heuristic
Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]
#算法刷题#The Machine Learning project including ML/DL projects, notebooks, cheat codes of ML/DL, useful information on AI/AGI and codes or snippets/scripts/tasks with tips.
#计算机科学#This is a repository which contains all my work related Machine Learning, AI and Data Science. This includes my graduate projects, machine learning competition codes, algorithm implementations and rea...
[Coursera] Reinforcement Learning Specialization by "University of Alberta" & "Alberta Machine Intelligence Institute"
#自然语言处理#A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.
DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN
Deep Reinforcement Learning Algorithms implemented with Tensorflow 2.3
Solving POMDP using Recurrent networks
PyTorch Implementation of Implicit Quantile Networks (IQN) for Distributional Reinforcement Learning with additional extensions like PER, Noisy layer, N-step bootstrapping, Dueling architecture and p...
#算法刷题#Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
#计算机科学#Implementation of Tsallis Actor Critic method
#计算机科学#ML-AI Community | Open Source | Built in Bharat for the World | Data science problem statements and solutions
PyTorch implementation of the Munchausen Reinforcement Learning Algorithms M-DQN and M-IQN
PyTorch implementation of the state-of-the-art distributional reinforcement learning algorithm Fully Parameterized Quantile Function (FQF) and Extensions: N-step Bootstrapping, PER, Noisy Layer, Dueli...
#区块链#A trading bitcoin agent was created with deep reinforcement learning implementations.