Working With Imbalanced Data for ML - Demonstrated Using Liver Disease Data

Working With Imbalanced Data for ML - Demonstrated Using Liver Disease Data

Explore techniques for handling imbalanced datasets in machine learning using Indian Liver Disease data as a practical example. Learn how to improve model accuracy through data up-scaling and SMOTE for minority classes. Dive into data visualization with spider plots and DataFrames, and understand the implementation of ROC AUC curves using Yellowbrick. Access the complete code demonstrated in the video through the provided GitHub repository link.