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 currently a student researching NLP and ML models and your research is amazing, and I would love to learn more from it.
I would greatly appreciate it if you could share your code for BERT and the GAN parts of this notebook, so that I can deepen my understanding of the subject.
Dear Boris,
I am currently a student researching NLP and ML models and your research is amazing, and I would love to learn more from it.
I would greatly appreciate it if you could share your code for BERT and the GAN parts of this notebook, so that I can deepen my understanding of the subject.
Thank you, Udai Khattar Cornell '23