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anq

askcos

combinatorial-bandit

A method to search for a subset of best performing items wrt black-box reward function

deep-reinforcement-learning-in-stock-trading

Using deep actor-critic model to learn best strategies in pair trading

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

flaml

A fast and lightweight AutoML library.

forex-rl-challenge

A Deep Reinforcement Learning Challenge on Forex Portfolio Management

puppet

将交易端的界面操作包装为交易接口，UIAutomation API for trade client. QQgroup：624585416

quantaxis

QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权/港股/虚拟货币 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

tick

Module for statistical learning, with a particular emphasis on time-dependent modelling