In this session a popular dataset from Kaggle will be selected and run through the Azure AutoML Pipeline. While the cloud machines methodically crunch the numbers on the best auto-generated model, I will hand-build a simple model in an Azure Jupyter Notebook over the same dataset. In this session participants will learn basic machine learning engineering techniques such as data preparation, feature engineering, and model tuning. We will wrap up with a discussion of the results and decide who built a better model - man or the machine!