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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.

XML sources of SICP and SICP JS, and support for generating Interactive SICP JS, PDF, e-book and comparison editions

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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.