Stock-Market Stock Market Prediction & Trading Bot using AI NOTE: AN IMPROVED VERSION OF THIS PROJECT WITH A WEB INTERFACE IS PRESENT HERE Stock Market Prediction using an LSTM Network Long Short Term Memory networks – usually just called “LSTMs” – are a special kind of RNN, capable of learning long-term dependencies. They were introduced by Hochreiter & Schmidhuber (1997), and were refined and popularized by many people in following work. They work tremendously well on a large variety of problems, and are now widely used. LSTMs are explicitly designed to avoid the vanishing gradient problem. All recurrent neural networks have the form of a chain of repeating modules of neural network. In standard RNNs, this repeating module will have a very simple structure, such as a single tanh layer. LSTMs also have this chain like structure, but the repeating module has a different structure. Instead of having a single neural network layer, there are four, interacting in a very special way. For more info check out this article Stock Market Agent using Evolution Strategy Agent Even though the

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