Experiments in Supervised Learning Part 4

Speeding up the Training Loop When developing and evaluating different machine learning models, rapid iteration is key—especially as experiments shift from feature engineering to focused model evaluation. At this stage, we want to make it as fast as possible to rerun training and testing cycles, particularly since feature extraction can become a bottleneck if performed repeatedly on the same data.…