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.
Firstly, thank you for sharing your knowledge with us. I am a college student majoring in data science I am very interested in your project. However, I am still a little confused about some details, including how to construct the GAN and connect all the project to predict and optimize.
Therefore, if possible, I would like to get a better look at your code. Could you please send the code to the following email address: 3210105936@zju.edu.cn.
Halo Boris,
Firstly, thank you for sharing your knowledge with us. I am a college student majoring in data science I am very interested in your project. However, I am still a little confused about some details, including how to construct the GAN and connect all the project to predict and optimize. Therefore, if possible, I would like to get a better look at your code. Could you please send the code to the following email address: 3210105936@zju.edu.cn.
Thank you very much!!!
Best wishes, Anchor.