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This project analyzes and develop a model to analyze and predict the sentiment given the costomer review for an amazon baby product. Turicreate is used for this work. The data set is highly biased towards the positive sentiment, so model is improved, by using only selected features for training the model.

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MuafiraThasni/Sentiment-Analysis-of-Amazone-Baby-Product-

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Sentiment-Analysis-of-Amazone-Baby-Product-

This project analyzes and develop a model to analyze and predict the sentiment given the costomer review for an amazon baby product. Turicreate is used for this work. The data set is highly biased towards the positive sentiment, so model is improved, by using only selected features for training the model.

Exploring the Data

Examining the most reviewed product

Rating for the most reviewed product

Product rating analysis as general

Sentiment Analysis

0 - 1 is for negative sentiment, and 1-2 is for positive sentiment

Model Development

Developed model uses Logistic Regression algorithm. Performance metrics:

  • 'f1_score': 0.9157860082304526,
  • 'log_loss': 0.39622654670874996,
  • 'precision': 0.8487520595594068,
  • 'recall': 0.9943165570488991

For code: Notebook

About

This project analyzes and develop a model to analyze and predict the sentiment given the costomer review for an amazon baby product. Turicreate is used for this work. The data set is highly biased towards the positive sentiment, so model is improved, by using only selected features for training the model.

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