Much of the public discourse in Data Science focuses on model optimization (selection of regressors/classifiers, hyperparameter tuning, model training and improvment of the prediction accuracy). Less material is available on using and deploying these trained Machine Learning models in production.
Building End-to-End Production Machine Learning pipelines
