Scikit-learn 1.9: Monitoring Model Training with Callbacks

scikit-learn 1.9 comes with a number of useful additions, and callbacks are one of them. Traditionally, when you call model.fit() in scikit-learn, you see the result only when fitting is complete. You do not see what is happening while the model is training. ➡️ Callbacks are objects that give you a way to observe what is happening during the training loop. This is especially useful when fitting takes longer, such as during cross-validation. So. Instead of seeing only the final result, you can track progress and record metrics throughout fitting. The image below shows two built-in callbacks in 1.9 which involve minimal code setup: 1️⃣ ProgressBar, which gives you a live view of the fitting work. 2️⃣ ScoringMonitor, which keeps a history of metrics that you can inspect afterwards. • You can read more about it here: https://lnkd.in/d69j-4SE • Also Probabl’s YouTube channel has a few useful short videos on the scikit-learn 1.9 highlights, including callbacks.