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.

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. 

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. 

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!