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PracticalApplication2

Business understanding of the problem:

A dataset with information on over 400 thousand used cars was provided. I prepared the dataset, experimented with different parameters to build models, and evaluated the model using the test set.

Findings:

I analyzed the dataset to identify that the features, including odometer, year, and fuel type, most strongly influence the target variable, car price.

Next steps:

The dataset contained substantial missing data, particularly in the manufacturer, condition, and title_status columns. As a result, I dropped these columns. However, lots of valuable information could be extracted.

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