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borisbanushev / stockpredictionai

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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Request for GAN code #202

Closed nvv11 closed 3 years ago

nvv11 commented 4 years ago

Thank you for sharing your ideas on git. This is an excellent work! Could you please share the complete source code?

siyutian8888 commented 4 years ago

Hi Boris, Go Bears! Thanks for sharing your work on GAN. I was wondering what the input for CNN(the discriminator) was. The output for the generator is the price, which is a number, but the input for CNN usually has 3 dimensions. Could you please share your ideas on that. I really appreciate if you could share your code or ideas on that part. Thanks! Best, Michael

Nasrin15 commented 3 years ago

Hello Boris,

Thanks for sharing your amazing work. I would also like to request GAN code with LSTM.