calmTeenager

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。

XAI-on-CIFAR-dataset-using-SHAP-DeepExplainer-

This is example on how to use SHAP's DeepExplainer to explain which part of image is focused ( learnt) to predict output class.

SimpleCNN-with-SHAP

Explainability_for_Photonics

Here, we use Deep SHAP (or SHAP) to explain the behavior of nanophotonic structures learned by a convolutional neural network (CNN). Reference: https://pubs.acs.org/doi/full/10.1021/acsphotonics.0c01067

SHAPObjectDetection

SHAP-Based Interpretable Object Detection Method for Satellite Imagery

shap

A game theoretic approach to explain the output of any machine learning model.

Train_Custom_Dataset

标注自己的数据集，训练、评估、测试、部署自己的人工智能算法

External-Attention-pytorch

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

approachingalmost

Approaching (Almost) Any Machine Learning Problem

PyTorch_Tutorial

《Pytorch模型训练实用教程》中配套代码

CapsNet

A pytorch implementation of Capsule Network.

StackGAN

rl-book

Source codes for the book "Reinforcement Learning: Theory and Python Implementation"

FinRL

FinRL: Financial Reinforcement Learning. 🔥

tianshou

An elegant PyTorch deep reinforcement learning library.

Deep-Reinforcement-Learning-Algorithms-with-PyTorch

PyTorch implementations of deep reinforcement learning algorithms and environments

omnisafe

OmniSafe is an infrastructural framework for accelerating SafeRL research.

Safe-Policy-Optimization

NeurIPS 2023: Safe Policy Optimization: A benchmark repository for safe reinforcement learning algorithms

cpo

Constrained Policy Optimization

computer-exemption

计算机类保研准备

CS-BAOYAN-2023

jsjby_2023

发布23年计算机保研夏令营和预推免通知，往年的保研经验帖；需要带保研或计算机保研资料联系qq：1585601434

SLM-Lab

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

cleanrl

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

revisiting-ppo

DeepReinforcementLearningInAction

Code from the Deep Reinforcement Learning in Action book from Manning, Inc

ganhacks

starter from "How to Train a GAN?" at NIPS2016

PlotNeuralNet

Latex code for making neural networks diagrams

leedl-tutorial

《李宏毅深度学习教程》（李宏毅老师推荐👍），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

Deep-Reinforcement-Learning-Algorithms

32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.