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 am learning ML for predicating the stock pricing and plan to share what i learnt with my colleagues. I googled and found your work on this area is quite impressive and i am willing to grasp all the ideas. Could you please share the full code with me? as the code snippet in tds & here is not fully functional.
thank you.
My mailbox: jay.han@dbschenker.com
Hi Boris:
i am learning ML for predicating the stock pricing and plan to share what i learnt with my colleagues. I googled and found your work on this area is quite impressive and i am willing to grasp all the ideas. Could you please share the full code with me? as the code snippet in tds & here is not fully functional. thank you. My mailbox: jay.han@dbschenker.com
Regards, Jay