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Stock Price Prediction using Recurrent Neural Network - Tensorflow

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Stock prediction model using RNN

This notebook demonstrates the future price prediction of SBI stock using recurrent neural network (RNN) in tensorflow. It also demonstrates a technique to identify the sudden attacks that occur in the stock prices and mitigate their impact on the stock prediction trends.

Prerequisites

Python3 Jupyter-notebook

This book has been developed on windows system with anaconda environment.

Important Repositories/packages

pandas numpy matplotlib sklearn math datetime os tensorflow

Installing

In anaconda prompt command pip install 'Package name' would install the required package along with all the dependencies.

Otherwise one can also use conda installation. For more details check out https://docs.conda.io/projects/conda/en/latest/commands/install.html

For linux based systems pip install package commands can be directly run from normal command prompt to download package and its dependencies.

To install tensorflow one can use 'conda install -c conda-forge tensorflow' if the above commands doesn't work

pip install pandas
or 
conda install pandas

Built With

  • [Python3]
  • [Anaconda]
  • [Juyter-notebook]
  • [Tensorflow]

Authors

  • Imran Quraishi

Acknowledgments

  • Raoul Malm - NY Stock Price Prediction RNN LSTM GRU
  • Sudarshan Deshmukh

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Stock Price Prediction using Recurrent Neural Network - Tensorflow

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