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TEAM

Predictive Modeling of Loan Default Risk Using Machine Learning and Natural Language Processing Techniques

Mandela Quashie, Uriel Gonzalez, Reid Harris, Omeiza Olumoye

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This project predicts loan default risk using Machine Learning (ML) and Natural Language Processing (NLP), leveraging HDF5 for efficient data storage and Apache Spark for large-scale data processing. Structured and unstructured data will be analyzed, with ML models trained on Spark and NLP techniques extracting insights from text. The final model will be evaluated on accuracy, precision, and AUC-ROC, providing a comprehensive tool for assessing lending risks.

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