stock,股票系统。使用python进行开发。
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.
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
最近一年贡献:0 次
最长连续贡献:0 日
最近连续贡献:0 日
贡献度的统计数据包括代码提交、创建任务 / Pull Request、合并 Pull Request,其中代码提交的次数需本地配置的 git 邮箱是 Gitee 帐号已确认绑定的才会被统计。