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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.

Translated:books: 《Go语言定制指南》 (Go Language Customization Guide) (formerly titled: Introduction to Go Syntax Trees / Open-Source Free Book / Advanced Go / Mastering Abstract Syntax Trees / Go Language AST)

A curated list of awesome CMake resources, scripts, modules and examples.

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A categorized list of C++ resources.

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Promise packages, patterns, chat, and tutorials

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