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marcap

market cap datasets (1995~2021 daily, 10 million+ rows)

market_simulator

Market simulator

mitigating-overfitting-experiment

Necessary code to reproduce the experiment in "Mitigating Overfitting with Generative Adversarial Networks"

mplfinance

Financial Markets Data Visualization using Matplotlib

mtss-gan

MTSS-GAN: Multivariate Time Series Simulation with Generative Adversarial Networks (by @firmai)

nab

The Numenta Anomaly Benchmark

networkx-projects

Using networkx module and Gephi tools

neural_graph_collaborative_filtering

Neural Graph Collaborative Filtering, SIGIR2019

ngcf-pytorch

PyTorch Implementation for Neural Graph Collaborative Filtering

ngcf_pytorch_g61

A reproducting of the Neural Graph Collaborative Filtering algorithm in PyTorch

nips2015_vrnn

pyfolio

Portfolio and risk analytics in Python

python

All Algorithms implemented in Python

pytorch-gan

PyTorch implementations of Generative Adversarial Networks.

pytorch-gan-timeseries

GANs for time series generation in pytorch

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. An increasing number of SOTA Quant research works/papers are released in Qlib.

recbole

A unified, comprehensive and efficient recommendation library

recommenders

Best Practices on Recommendation Systems

research_public

Quantitative research and educational materials

reviewduk

Korean Sentiment Analyzer in Morphologically Rich Languages

social-distancing-in-theater-with-profit-maximization

IE50501 Linear Programming Final Project

systrader

파이썬을 이용한 자동 주식투자 시스템

tadgan

Code for the paper "TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks"

tadgan-1

TadGAN for T.F 2.0

tanogan

technical_indicators

Python 을 통해 기술적 지표를 익혀 봅시다~

tf-quant-finance

High-performance TensorFlow library for quantitative finance.

timegan

Codebase for Time-series Generative Adversarial Networks (TimeGAN) - NeurIPS 2019

ultragcn

[CIKM'21] UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation

unist_homeworks

Homeworks repository