Deploying, Monitoring, and Scaling in Production
Some people may read this book from beginning to end to gain an overall understanding of as many concepts as possible in the realm of AI/ML on Google Cloud, while others may use it as a reference, whereby they pick it up and read certain chapters on specific topics whenever they need to work with those topics as part of a project or client engagement. If you’ve been reading this book from the beginning, then you have come a long way, and we have journeyed together through the majority of the ML model development life cycle (MDLC). While model training is what often gets the most attention in the press – and that is where a lot of the magic happens – you know by now that training is just one piece of the overall life cycle.
When we’ve trained and tested our models, and we believe they’re ready to be exposed to our clients, we need to find a way to host them so that they can be used accordingly. In...
