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In this Machine Learning project, you will build a classification model in python to classify the reviews of an app on a scale of 1 to 5 using Gated Recurrent Unit.
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Gated Recurrent Unit(GRU) is an improved version of the standard Recurrent Neural Network(RNNs). As a variant of the recurrent neural network, they are able to process memories of sequential data by storing previous inputs in the internal state of networks and plan from the history of previous inputs.
In this project, an application review classification model has been built using GRU. The project focuses on classifying the review of the application based on a 1 to 5 scale with 1 being negative sentiment and 5 being positive sentiment. If you haven’t visited already, here is the previous project of the series Build CNN Image Classification Models for Real Time Prediction
To understand the Gated Recurrent Unit
To classify the review of an app on a scale of 1 to 5 using Gated Recurrent Unit
The dataset contains the reviews and the ratings of the app. The dataset has a score column and content column. The score columns have a number range between 1 to 5 based on the content column.
Language: Python
Libraries: pandas, tensorflow, matplotlib, sci-kit learn, pillow, gunicorn, textblob, nltk, keras, flask
Converting words to lower case
Lemmatization of the words
Tokenization of the words
One hot encoding of the scores
Training sequential model in Tensorflow
Evaluation of model on test data
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