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Implemented Sentiment Analysis to analyze product reviews of products sold online using Turicreate library.

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Sentiment Analysis of Product Reviews

In this project, I have implemented the conecept of Sentiment Analysis to analyze product reviews of some products from online stores and used them to determine the sentiment of the user like for example if they liked the specific product or not based on a count of positive and negative words used in the product review.

To get started download the SFrame used by this project from here: https://d3c33hcgiwev3.cloudfront.net/y4OKQuIFEemJfgqR2HI2sA_43be9d356abf4561888105f8045995bf_amazon_baby.sframe.zip?Expires=1648339200&Signature=JBH3~lxwz2z4wq9EwGj4LNOHyamhlF-aquaiAZEFmXm4hqpIjZCHQceEA2Os-Hced8eiEyvpYncqi3RoSeMPceBh6kSSKHx0ze9RPZb91rwGe2azn7BUhiFfQ4xqRSU56TXRgmHwVhRUHQjjftN-n8Yl3yPzvRicuhnsJ8KTO6E_&Key-Pair-Id=APKAJLTNE6QMUY6HBC5A.

Unzip the folder obtained from the link and look for the file called as m_bfaa91c17752f745.0000.Then move this file to the folder amazon_baby.sframe that is present in the same folder as this README.md file.

Next follow the instructions in the jupyter notebook and carry on. Thank You. Referred from Machine Learning Foundations: A Case Study Approach from Coursera.

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Implemented Sentiment Analysis to analyze product reviews of products sold online using Turicreate library.

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