Chapter 17: Preparing for a Successful ML Journey
Congratulations, you've made it – what an incredible journey you've been on! By now, you should have learned how to preprocess data in the cloud, experiment with ML models, train deep learning models and recommendation engines on auto-scaling clusters, optimize models, and deploy them wherever you want. And you should know how to add a cherry to the top of the cake by operationalizing all of these steps through MLOps.
In this last chapter, we will recap some important revelations we learned during this journey. It's easy to get lost or overwhelmed by technological and algorithmic choices. You could dive deep into modeling, infrastructure, or monitoring without getting any closer to having a good predictive model.
In the first section, we will remind you that ML is mostly about data. Artificial intelligence should probably be called data cleansing and labeling, but of course, this doesn't sound as good...