SC1015 Data Science Project Group Members: Aaron, Ivan, Yifei
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10% for coming up with your own problem definition based on a dataset
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10% for data preparation and cleaning to suit the problem of your choice
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20% for exploratory data analysis/visualization to gather relevant insights
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20% for the use of machine learning techniques to solve specific problem
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20% for the presentation of data-driven insights and the recommendations
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10% for the quality of your final team presentation and overall impressions
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10% for learning something new and doing something beyond this course
- Machine learning main goal: predict rating of the app using features.
- Which genre of apps has the highest rating?
- Which country makes the best apps?
- Does content rating, price(free / paid), ad supported apps has impact on the rating?
- Does size of the app affect total installs? (some people don't like to install large apps)
- Which type of games is the most successful?
- Best developers and their top categories.
- Developers that made the most apps.
- FAANG, which company made the best apps?
- How to get "High" Rating on Play Store?
Dataset link: google-playstore-apps
Scrapper folder ./google-play-scrapper
Problem 1: Predicting the rating of the app (Numerical)
Linear Regression
Problem 2: Prediciting the app price (free/paid)
Classification
Problem 3: Predicting size of the app?
Streamlit link