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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.

Learn Express.js from the author of one of the best books on Express.js—Pro Express.js— with this workshop that will teach you basics of Express.js.

TranslatedJava Web project demo. Backend: spring + spring mvc + mybatis + maven, covering the quartz scheduled tasks, ehcache caching, RESTful API, email sending... Frontend: react + reflux + webpack, covering ES6, jquery, react-router, ant design, etc. Provides some ideas, for reference only.