HomeUpcoming webinars

Running Machine Learning Experiments in Python

Key Takeaways:
  • Understand the complete machine learning pipeline, from conception to production and beyond..
  • Learn how to form a machine learning experiment to compare versions of models.
  • Learn how to use MLflow to manage a machine learning experiment pipeline.
Tuesday November 14, 11AM ET
View More Webinars

Register for the webinar

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.


The machine learning workflow doesn't end with making a prediction: you often want the model to be used in production. That means using MLOps techniques to make the model available, to conduct experiments to improve the performance, and to maintain it.

In this webinar, you'll use MLflow to manage a machine learning experiment pipeline. The session will cover model evaluation, hyperparameter tuning, and MLOps strategies, using a London weather dataset.

Presenter Bio

Folkert Stijnman Headshot
Folkert StijnmanFounder at folkert.data

Folkert provides data science and machine learning consultancy services to companies. He previously worked as a machine learning engineer at Enjins, and is the instructor of DataCamp's "MLOps Concepts" course and the "Predicting Temperature in London" project.

View More Webinars