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.
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bruh vae_data is just the combined features data. Since it literally says "VAE used for higher level feature extraction" so from the talk it holds that VAE_Data=(PRICE+AIRMA+FFT+CORRELATED ASSET DATA+.....).. all implementation of this notebook will be UNIQUE except for the AI part #353
bruh vae_data is just the combined features data. Since it literally says "VAE used for higher level feature extraction" so from the talk it holds that VAE_Data=(PRICE+AIRMA+FFT+CORRELATED ASSET DATA+.....).. all implementation of this notebook will be UNIQUE except for the AI part
sir，i'm learning High Frequency Trading， can u please provide full code for giving me some help ,thank u very much,my email is 765800916@qq.com
thanks!
Originally posted by @IISuperluminaLII in https://github.com/borisbanushev/stockpredictionai/issues/18#issuecomment-651355601
sir，i'm learning High Frequency Trading， can u please provide full code for giving me some help ,thank u very much,my email is 765800916@qq.com thanks!