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Recurrent Neural Network to predict the next app to be used, using Python and Keras.

Python 100.00%
python27 keras-neural-networks keras-models recurrent-neural-networks rnn-model lstm-neural-networks lstm-model deep-neural-networks neural-networks prediction app-prediction python tensorflow

lstm-for-predicting-the-next-app-to-use.'s Introduction

Predicting-the-next-app-to-use.

This is a LSTM(Long-Short Term Memory)-Recurrent neural network model that helps to predict the next app a user might use based on his previous app usage data. The Dataset contains around 2000 datapoints reflecting all the applications that were used by a user within 1 week.

Since only 36 apps were used by the user in that particular week, the prediction is limited to the 36 apps.

To reuse the already trained model:

python src/generateModel.py True

To generate and train a new model:

python src/generateModel.py

The same "dataset.csv" is divided into training and test data. Since our mobile phone's usually contain around 4 app suggestion space, we take the first 4(with the highest probability) predicted apps ,to test the accuracy of our model.

"actual_app_used" variable is a dataframe that contains the actual apps that were used by the user. And "prediction" variable is a dataframe that contains the predicted apps of the model during the same instance.

Final Output-

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