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fortunesuyue's Projects

30-days-of-python

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.

aihongsunphd-thesis-projects

This repository contains the code of the deep MARL-based dynamic scheduling algorithms in job shop and flexible job shop

annotated_deep_learning_paper_implementations

🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

awesome-pretrained-chinese-nlp-models

Awesome Pretrained Chinese NLP Models，高质量中文预训练模型集合

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

book-mathmatical-foundation-of-reinforcement-learning

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

captainblackboard

船长关于机器学习、计算机视觉和工程技术的总结和分享

chinese-text-classification-pytorch

中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。

cnn-bigru-am

This repository includes code for the paper: Lithology Identification Based on One-dimensional Convolutional Neural Network and Recurrent Neural Network with Attention Mechanism.

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deep-learning-with-pytorch-book

PyTorch深度学习开源电子书

deep-learning-with-tensorflow-book

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

deeplabv3-plus

Tensorflow 2.3.0 implementation of DeepLabV3-Plus

elegantrl

Massively Parallel Deep Reinforcement Learning. 🔥

evolutionary-reinforcement-learning

Codebase for Evolutionary Reinforcement Learning (ERL) from the paper "Evolution-Guided Policy Gradients in Reinforcement Learning" published at NeurIPS 2018

experimentaltools4deeplearning

notebook for Deep Learning tools

external-attention-pytorch

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

free-programming-books

:books: Freely available programming books

gdn-ts-gnn-

Implementation code for the paper "Graph Neural Network-Based Anomaly Detection in Multivariate Time Series"

github

GitHub 漫游指南- a Chinese ebook on how to build a good project on Github. Explore the users' behavior. Find some thing interest.

howtolivelonger

程序员延寿指南 | A programmer's guide to live longer

hrnet-semantic-segmentation

This is an official implementation of semantic segmentation for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919

imbalanced-regression

[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

mtad-gat-pytorch

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

multi-agent-reinforcement-learning-foundations-and-modern-approaches

MARL-Book's official codebase repo. www.marl-book.com ; Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

nnoptimizer_agd

Automatic Gradient Descent: Deep Learning without Hyperparameters

paper-sgcn

Split Depth-wise Separable Graph Convolution Network for Road Extraction in Complex Environment from High-resolution Remote Sensing Imagery

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