MLOps with MLflow - Creating Execution Pipelines Using Projects and Databricks
Offered By: The Machine Learning Engineer via YouTube
Course Description
Overview
Explore MLflow Projects and learn how to create execution pipelines locally while utilizing Databricks as a Tracking Server and Artifacts Repository in this 18-minute video tutorial. Discover the process of working with projects in MLflow and gain hands-on experience in implementing machine learning operations (MLOps) techniques. Access the accompanying code on GitHub to follow along and enhance your understanding of MLflow pipelines and their integration with Databricks.
Syllabus
MLOps MLFlow: Mlflow Projects: Databricks and MLflow pipelines #machinelearning
Taught by
The Machine Learning Engineer
Related Courses
Data Processing with AzureLearnQuest via Coursera Mejores prácticas para el procesamiento de datos en Big Data
Coursera Project Network via Coursera Data Science with Databricks for Data Analysts
Databricks via Coursera Azure Data Engineer con Databricks y Azure Data Factory
Coursera Project Network via Coursera Curso Completo de Spark con Databricks (Big Data)
Coursera Project Network via Coursera