This document is intended to help those with a basic knowledge of machine learning get the benefit of Google’s best practices in machine learning. It presents a style for machine learning, similar to the Google C++ Style Guide and other popular guides to practical programming. If you have taken a class in machine learning, or built or worked on a machine-learned model, then you have the necessary background to read this document.
Five parts to the document:
- Understand whether the time is right for building a machine learning system.
- Deploying first pipeline
- Launching and iterating while adding new features to your pipeline, how to evaluate models and training-serving skew.
- What to do when you reach a plateau.
- List of related work and an appendix.