Designing Machine Learning Workflows in Python Data Camp

Overview

Context

Deploying machine learning models in production seems easy with modern tools, but often ends in disappointment as the model performs worse in production than in development. 

This Designing Machine Learning Workflows in Python course offered by Data Camp will give you four superpowers that will make you stand out from the data science crowd and build pipelines: how to exhaustively tune every aspect of your model in development; how to make the best possible use of available domain expertise; how to monitor your model in performance and deal with any performance deterioration; and finally how to deal with poorly or scarcely labelled data. 

Digging deep into the cutting edge of sklearn, and dealing with real-life datasets from hot areas like personalized healthcare and cybersecurity, this course reveals a view of machine learning from the frontline.