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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.

Open source, self-hostable watched list for all your content (movies, tv series, anime, games) with user authentication, modern and clean UI and a very simple setup.

Tools and packages that are used for countering forensic activities, including encryption, steganography, and anything that modify attributes. This all includes tools to work with anything in general that makes changes to a system for the purposes of hiding information.

A general-purpose lightweight C++ graph library

  • graph
  • bfs
  • dfs
  • graph-algorigthms

Simple Genetic Algorithm for demonstration purposes

  • genetic-algorithm
  • evolutionary-algorithms
  • evolutionary-algorithm
  • evolutionary-computation