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Repositories
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
A collection of CTR prediction models in PyTorch.
some ctr model, implemented by PyTorch, such as Factorization Machines, Field-aware Factorization Machines, DeepFM, xDeepFM, Deep Interest Network
搜狐算法大赛：主要实体词情绪识别 baseline
量化投资中各类指标的择时策略的实现，基于JoinQuant回测平台。
Entity and Relation Extraction Based on TensorFlow. 基于TensorFlow的管道式实体及关系抽取，2019语言与智能技术竞赛信息抽取任务解决方案（比赛结束后完善代码）。Schema based Knowledge Extraction, SKE 2019
Backtesting for sleepless cryptocurrency markets
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
Python Backtesting library for trading strategies
Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier — compact, simple and fast
Financial markets analysis framework for programmers
MooQuant 是一个基于 pyalgotrade 衍生而来的支持 python3 的支持国内A股的量化交易框架。
Zipline, a Pythonic Algorithmic Trading Library
Essential Cheat Sheets for deep learning and machine learning researchers
Materials related to the Medium article "Predicting Stock Prices with Echo State Networks".
Repository for Going Deeper with Convolutional Neural Network for Stock Market Prediction
tf-recsys contains collaborative filtering (CF) model based on famous SVD and SVD++ algorithm. Both of them are implemented by tensorflow in order to utilize GPU acceleration.
Collaborative Deep Learning (CDL)
recommendation system contains PMF、ConvMF、JMF、MLP models