Objectives
- Think strategically and analytically about ML as a business process and consider the fairness implications with respect to ML
- How ML optimization works and how various hyperparameters affect models during optimization
- How to write models in TensorFlow using both pre-made estimators as well as custom ones and train them locally or in Cloud AI Platform
- Why feature engineering is critical to success and how you can use various technologies including Cloud Dataflow and Cloud Dataprep