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This article uses 2 important models for the predictions and comparisons. These are Long Short-Term Memory and Recurrent Neural Network measures. The result of LSTM and RNN are compared to check the most optimal model for stock forecasting. For this, various metrics and visualization are considered using different independent variables for both the models. We are going to estimate this using different plot criteria, RMSE value, and R2 score of different number of independent variables for both LSTM and RNN.

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artificial-neural-networks jupyter-notebook lstm-neural-networks machine-learning matplotlib numpy python-3 rmse-score rnn seaborn sklearn stock-market stock-price-prediction tensorflow

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