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TranslatedThe original of this article was written by the well-known hacker Eric S. Raymond. It teaches you how to ask technical questions correctly and get answers you are satisfied with.

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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.

Inspired by @veltman's command-line mystery, use SQL to research clues and find out whodunit!

📗 How to write cross-platform Node.js code

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