Coders Packet

Loan Status Prediction using Python

By Vyankatesh Khandke

Is the person eligible for a loan or not, and the solution for this is using this Loan Status Prediction.

Of all industries, insurance makes the most use of analytical and data science techniques. This dataset provides enough taste to manipulate insurer datasets, challenges, strategies used, variables that influence outcomes, and more. This is a classification issue. The data has 615 rows and 13 columns.

Problems:  The company wants to automate the credit scoring process (in real time) based on the customer data provided when filling out the online application form. These details include gender, marriage history, education, number of dependents, income, loan amount, credit history, and more. To automate this process, they combined the problem of identifying the customer segments for which the loan amount was targeted, allowing them to be targeted. Here they provided a partial dataset.

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