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.
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Enhanced Version of Boris Banushev’s Stock Prediction System Available #373
I've seen a lot of interest in obtaining the source code for Boris Banushev's stock prediction system. I wanted to let you know that I have developed a comprehensive version of this system, incorporating all necessary features and enhancements based on the original concept.
Key Features:
Enhanced data preprocessing and feature engineering.
Improved LSTM and GAN architecture for better prediction accuracy.
Comprehensive documentation and setup guides.
If you're interested in acquiring this version or would like more details, please feel free to reach out to me directly at yamankhetan@ymail.com
I'm happy to provide further information and discuss how this system can meet your needs.
Hi everyone,
I've seen a lot of interest in obtaining the source code for Boris Banushev's stock prediction system. I wanted to let you know that I have developed a comprehensive version of this system, incorporating all necessary features and enhancements based on the original concept.
Key Features:
If you're interested in acquiring this version or would like more details, please feel free to reach out to me directly at yamankhetan@ymail.com
I'm happy to provide further information and discuss how this system can meet your needs.
Thank you, Yaman Khetan