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Data Project for the class Introduction to Data Science. Different regression algorithms were trained and tested using 0.5 million rows of data against each other.. The conclusion part is incomplete.

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Using ML Regression Algorithms to train and test Product Sales Data categorized by various attributes of the Customers

Columns

- User_ID	
- Product_ID
- Gender	
- Age	
- Occupation	
- City_Category	
- Stay_In_Current_City_Years	
- Marital_Status	
- Product_Category_1	
- Product_Category_2	
- Product_Category_3	
- Purchase

This was part of a Final Project for the "Introduction to Data Science" class.

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Data Project for the class Introduction to Data Science. Different regression algorithms were trained and tested using 0.5 million rows of data against each other.. The conclusion part is incomplete.

Topics

numpy sklearn pandas seaborn xgboost matplotlib

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