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.
For my seminar paper, I was looking for practicable examples for Neural Networks and found your project by accident. Your research and work are amazing. I would like to use your project as an inspiration in my work.
Would it be possible to get a copy of your final code?
Hello Boris,
For my seminar paper, I was looking for practicable examples for Neural Networks and found your project by accident. Your research and work are amazing. I would like to use your project as an inspiration in my work. Would it be possible to get a copy of your final code?
My email is: zachariah_black@outlook.com
Best wishes, Zachary