Predicting heart disease risk with a focus on minimizing false negatives. Implements advanced handling of class imbalance to build diagnostic tool.

The aim to decrease the maintenance cost of generators used in wind energy production machinery. This is achieved by building various classification models, accounting for class imbalance, and tuning on a user defined cost metric (function of true positives, false positives and false negatives predicted) & productionising the model using pipelines.