Integrating ML in Assessing Financial Risk: A Case Study

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Explore the intricacies of fraud detection with a focus on machine learning applications. The presentation examines the business problem of imbalanced transaction datasets emphasizing the necessity for precise metrics like precision, recall, and F1-score. Gain insights from Exploratory Data Analysis (EDA) to recognize fraud patterns and prepare data for effective modeling. Understand the benefits and limitations of various models including Logistic Regression, Random Forest, and Isolation...