Loan dataset refining and used numpy and other library

1. *Data preprocessing*: Handle missing values, scale numerical features, and encode categorical variables. 2. *Machine learning model*: Train a robust model using historical data t

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What it doespressure to make informed decisions about loan approvals. Manual processes can lead to biases, inefficiencies, and inaccurate assessments. This project aims to revolutionize the lending industry by harnessing the power of machine learning and data analysis.

Goal: Develop a predictive model that accurately determines loan eligibility based on

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