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erformed a predictive analysis on the customer's Bank Loan Application data to predict loan status. Using python, pandas, scipy, seaborn, AutoML libraries, and machine learning techniques. Used Machine Learning techniques to accurately predict the evaluation scheme if the particular loan will be 'Fully Paid' or 'Charged Off'. This means if Bank accepts a particular person's loan application will it be 'Fully Paid' or 'Charged Off'

License: MIT License

Jupyter Notebook 100.00%
visualization python seaborn predictive-modeling feature-selection pandas machine-learning automl machine-learning-algorithms model-interpretability

bank-loan-status-predictive-analysis's Introduction

  • ๐Ÿ‘‹ Hi, Iโ€™m Sanket Sanap
  • ๐Ÿ‘€ Iโ€™m interested in Big Data, Data Science, Data Engineering and Cloud applications
  • ๐ŸŒฑ Pursuing Master of Science in Data Architecture and Management
  • ๐Ÿ“ซ Reach me at [email protected]

bank-loan-status-predictive-analysis's People

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sanapsanket avatar sanketsanap5 avatar

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