Automated machine learning (AutoML) can automate time-consuming tasks in the machine learning lifecycle like data preprocessing, model training, and tuning. This allows data scientists to focus on higher-level work. The presentation demonstrated AutoML on the Titanic dataset in Microsoft Azure Machine Learning service. It showed how AutoML can iterate through various algorithms and hyperparameters, measure model performance, enable model interpretability, facilitate model hosting and drift detection, and support code-based MLOps workflows. AutoML aims to make machine learning more accessible and productive.