Pinned Repositories
AIOquant
Asynchronous event I/O driven quantitative trading framework.
alphahunter
异步事件驱动/量化交易/做市系统/策略研究/策略回测
AlphaTrading
An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implement APT model, BARRA's risk model and dynamic multi-factor model in this project.
awesome-python
A curated list of awesome Python frameworks, libraries, software and resources
awesome-reinforcement-learning-zh
中文整理的强化学习资料（Reinforcement Learning）
Barra-Model
An internship project: Implement Barra model to take risk or style factor attribution based on multi-factor model.
c-binance-futures-quant
low-cost, high-efficiency, easy-to-implement
caffe
Caffe: a fast open framework for deep learning.
CF
JsonAC's Repositories
JsonAC/AIOquant
Asynchronous event I/O driven quantitative trading framework.
JsonAC/alphahunter
异步事件驱动/量化交易/做市系统/策略研究/策略回测
JsonAC/AlphaTrading
An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implement APT model, BARRA's risk model and dynamic multi-factor model in this project.
JsonAC/awesome-reinforcement-learning-zh
中文整理的强化学习资料（Reinforcement Learning）
JsonAC/Barra-Model
An internship project: Implement Barra model to take risk or style factor attribution based on multi-factor model.
JsonAC/c-binance-futures-quant
low-cost, high-efficiency, easy-to-implement
JsonAC/chinese-ocr
基于CTPN（tensorflow）+CRNN（pytorch）+CTC的不定长文本检测和识别
JsonAC/Chinese-Transformer-XL
JsonAC/Chinese_Rumor_Dataset
中文谣言数据
JsonAC/deepbayes-2018
Seminars DeepBayes Summer School 2018
JsonAC/DELAFO-DeEp-Learning-Approach-for-portFolio-Optimization
JsonAC/FinRL-Library
A Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020. Please star. 🔥
JsonAC/gcn
Implementation of Graph Convolutional Networks in TensorFlow
JsonAC/GRAND
Source code and dataset of the NeurIPS 2020 paper "Graph Random Neural Network for Semi-Supervised Learning on Graphs"
JsonAC/graphsage-simple
Simple reference implementation of GraphSAGE.
JsonAC/HS300-1
沪深300指数纯因子组合构建
JsonAC/Informer2020
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
JsonAC/magenta
Magenta: Music and Art Generation with Machine Intelligence
JsonAC/notes-python
中文 Python 笔记
JsonAC/Poinchinski-Memories
Translation of professor Joseph Polchinski's article 'Memories of a Theoretical Physicist'
JsonAC/ProNE
Source code and dataset for IJCAI 2019 paper "ProNE: Fast and Scalable Network Representation Learning"
JsonAC/qlib
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.
JsonAC/shadowsocksr-csharp
JsonAC/shanghai_house_knowledge
2020年11月在上海买房经历总结出来的买房购房做的一些功课分享给大家，技术人帮助技术人，希望对大家有所帮助。
JsonAC/SingleModelUncertainty
Learning error bars for neural network predictions
JsonAC/Stock-Market-Price-Prediction
Analysis of various deep learning based models for financial time series data using convolutions, recurrent neural networks (lstm), dilated convolutions and residual learning
JsonAC/Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
JsonAC/thenextquant
Asynchronous driven quantitative trading framework.
JsonAC/transferlearning-tutorial
《迁移学习简明手册》
JsonAC/Wavenet-PyTorch
PyTorch implementation of Wavenet