MLflow: Managing the Machine Learning Lifecycle

In this hands-on course, data scientists and data engineers learn the best practices for managing experiments, projects, models, and a production model registry using MLflow. By the end of this course, you will have built a pipeline to train, register, and deploy machine learning models using the environment they were trained with. This course is taught entirely in Python and pairs well with the Machine Learning Deployment course.


 
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