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.
I really appreciate your great work. Thank you so much!
I am a student in the CUHK from Hong Kong, me and my friends are currently researching on machine learning and hope to reference your great work. Could you please share your code about GAN and RL hyper parameter optimization to us? We promise we would only take the code as academic purpose and will definitely give great credit to you if we have any significant progress.
Thank you so much for your great work. We sincerely appreciate your generosity. Wish you all the best.
heamabc
commented
4 years ago
I really appreciate your great work. Thank you so much!
I am a student in the CUHK from Hong Kong, me and my friends are currently researching on machine learning and hope to reference your great work. Could you please share your code about GAN and RL hyper parameter optimization to us? We promise we would only take the code as academic purpose and will definitely give great credit to you if we have any significant progress.
Thank you so much for your great work. We sincerely appreciate your generosity. Wish you all the best.