TranslatedCollecting all materials related to blockchain (BlockChain) technology development, including Fabric and Ethereum development materials
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TranslatedApacheCN collection of translated texts on data structures and algorithms
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.
Boilerplate Hapi server example. Node.js, Hapi, and Swig.