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.
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Reinforcement learning for hyperparameter optimization #12
i'm trying to improve this software by adding Reinforcement learning for hyperparameter optimization： Rainbow based on
Q-learnin and Proximal Policy Optimization (PPO).
Hi,
i'm trying to improve this software by adding Reinforcement learning for hyperparameter optimization： Rainbow based on Q-learnin and Proximal Policy Optimization (PPO).
has anyone ever worked on it?