How to Test and Monitor Machine Learning Model Deployments

Photo by Luis Gomes from Pexels

For years, businesses and developers have understood the importance of testing software before deployment. Before it can interface with customers in real time, a business naturally wants the software to function as expected. With the increasing demand for machine learning implemented in business, it’s reasonable to expect that machine learning models deployed into production need to be…

--

--

--

Lead Data Scientist, author of “Python Feature Engineering Cookbook”, instructor of machine learning at www.trainindata.com and developer of Python open-source.

Love podcasts or audiobooks? Learn on the go with our new app.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Sole from Train in Data

Sole from Train in Data

Lead Data Scientist, author of “Python Feature Engineering Cookbook”, instructor of machine learning at www.trainindata.com and developer of Python open-source.

More from Medium

About Ensemble Techniques in ML.

Machine Learning Case Study — Credit Card Fraud Detection

Kaggle — Black Friday dataset using XGBoost algorithm + Feature Engineering

Complete Feature Selection Techniques 4 - 4 Model Driven