Taming The Wild West: Feature Selection For Scalable ML
Imagine building a house with every brick, beam, and nail you can find. Sure, it might stand, but it’s likely to be over-engineered, expensive, and inefficient. The same principle applies to machine learning models. Including every possible feature doesn’t guarantee the best performance. In fact, it can lead to overfitting, increased computational cost, and reduced […]



