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ai_papers

AI Papers

algorithm

算法练习

ant-design

An enterprise-class UI design language and React UI library

attention-is-all-you-need-pytorch

A PyTorch implementation of the Transformer model in "Attention is All You Need".

awesome-ai-best-papers

A curated list of famous CV/NLP/ML/AI best papers, inspired by Best Paper Awards in Computer Science (since 1996).

back

本科毕业设计—后端

chineseocr

yolo3+ocr

circlesexperiment

使用LSTM预测从随机圆上截取序列的下一个点的坐标

classify

使用CNN分类图像的demo

ddpg-keras-torcs

Using Keras and Deep Deterministic Policy Gradient to play TORCS

ddz-ai

以孤立语假设和宽度优先搜索为基础，构建了一种多通道堆叠注意力Transformer结构的斗地主ai

deep-hedging

dhtcrawler2

dhtcrawler is a DHT crawler written in erlang. It can join a DHT network and crawl many P2P torrents. The program save all torrent info into database and provide an http interface to search a torrent by a keyword

distributedsystem

MIT分布式系统课程的实践项目

dqlearning-toolbox

A Toolbox for deep reinforcement learning(QLearning)

dqn-ddpg_stock_trading

Using DQN/DDPG for stock trading

fdrnn

Deep Direct Reinforcement Learning for Financial Signal Representation and Trading

gameaisdk

基于图像的游戏AI自动化框架

git-demo

interview_internal_reference

2019年最新总结，阿里，腾讯，百度，美团，头条等技术面试题目，以及答案，专家出题人分析汇总。

learning2rank

Learning to rank with neuralnet - RankNet and ListNet

mid-lstm-meets-mid-arma

Mid-LSTM meets Mid-ARMA: deep learning for midterm stock prediction.

multi-agent-emergence-environments

Environment generation code for the paper "Emergent Tool Use From Multi-Agent Autocurricula"

mynote

note

本科毕业设计-前端

papers-literature-ml-dl-rl-ai

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning

pgportfolio

PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).

plane_direct2d

本科时用 C++ DX2D 和 纯winSDK 写的雷霆战机游戏

pop-art-translation

Translation and understanding for the Pop-art paper.

principles

My Principles