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For models that take a long time to train, a notebook isn't always the most convenient option. If you're building an ML application, it's unlikely you'll only need to train your model once. Over time you'll want to retrain your model to make sure it stays fresh and keeps producing valuable results. Manually executing the cells of your notebook might be the right options when you're getting started with a new ML problem, but when you want to automate experimentation at scale or retrain models for a production application, a managed ML training option will make things much easier.