Stock Predictor Using LSTM Stock Predictor using LSTM is a machine learning model that predicts the future stock prices of a company based on its historical prices. LSTM (Long Short-Term Memory) is a type of recurrent neural network (RNN) that can process and predict sequences of data.
The Stock Predictor using LSTM uses historical stock prices as input data and predicts the future stock prices as output. The historical prices are usually represented as a time series, where each data point represents the stock price at a specific time.
The LSTM model consists of an input layer, a hidden layer, and an output layer. The input layer takes in the historical stock prices as input, and the output layer produces the predicted stock prices. The hidden layer contains LSTM units, which have a special memory cell that allows them to remember past information and decide what information to keep or discard.
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