Machine Learning in Production: MLflow and Model Deployment - Databricks

Machine Learning in Production: MLflow and Model Deployment

In this hands-on course, data scientists and data engineers learn best practices for managing experiments, projects, and models using MLflow. Students build a pipeline to log and deploy machine learning models, as well as explore common production issues faced when deploying machine learning solutions and monitoring these models once they have been deployed into production. By the end of this course, you will have built the infrastructure to track, deploy, and monitor machine learning models. This course is taught entirely in Python.



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