This project is about the city of Detroit where many residents have refused to pay their blight tickets so the city want to know how they can increase blight tickets compliance. The approach to solving this problem is to understand when & why a resident might fail to comply with a blight ticket. In order to get this I predicted if a given blight ticket will be paid on time or not using Gradient Boosting Classifier and AUC score for evaluating the model.
In this project, I did some analysis and i made inferences based on some particular questions using SQLite.
Firstly, I did some preprocessing to have good understanding of the dataset. then I compared the difference between business with high star rating and business with low star rating. then I predicted the major reasons why some businesses close down by comparing closed and active business. Lastly, I analyze the star rating and number of reviews to know popular food companies in Yelp.
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