hungchun-lin / Stock-price-prediction-using-GAN

In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.
MIT License
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some questions #6

Closed CrimsonCyborg closed 3 years ago

CrimsonCyborg commented 3 years ago

Because there is no comment, I want to ask where there is a train predict index.npy?

hungchun-lin commented 3 years ago

Please see: https://github.com/hungchun-lin/Stock-price-prediction-using-GAN/issues/5