Predicting installs on
Google Playstore
I believe in constantly adding to my toolbox of skills and therefore took an Applied Machine Learning class to understand how data can be utilized to predict user behavior in a variety of situations.
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The aim of this project was to use the Google Play Store dataset and predict the number of installs for each category of app based on ratings, reviews and price.
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I got the Google Play Store dataset which had the attributes App, Category, Rating, Reviews, Size, Installs, Type, Price, Content rating, Genres, Last updated, Current ver, Android ver. I found quite a deep breath of work on this dataset and therefore was intrigued to use that as my inspiration.
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The dataset was taken from Kaggle and was created by Lavanya Gupta
Here is a link to my complete project report and prediction findings. As I am a beginner in this phase, I would really appreciate people's feedback on this!