Fixes #772 Playstore Rating Prediction #774
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👋 Thank you for opening this pull request! We appreciate your contribution to improving this project. Your PR is under review, and we'll get back to you shortly. To help move the process along, please tag @UppuluriKalyani, @Neilblaze, and @SaiNivedh26 for a faster review! |
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Nov 5, 2024
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🎉🎉 Thank you for your contribution! Your PR #774 has been merged! 🎉🎉 |
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Related Issues or bug
Given a dataset of Google Play Store applications with attributes such as app category, size, price, and other metadata, the objective is to develop a predictive model that estimates an app's rating based on these attributes. This will allow stakeholders to identify the factors that most significantly influence app ratings and make data-driven improvements to their applications.
Fixes: #772
Proposed Changes
This project involves building a machine learning model to predict the ratings of applications on the Google Play Store. Using a range of app-specific features (like category, reviews, size, type, price, content rating, genres, and Android version), the model aims to accurately predict app ratings. This project helps understand how different app attributes affect the rating, enabling app developers to make informed design and feature decisions to optimize user satisfaction.