Machine Learning Model Development 

This comprehensive course provides a practical guide to developing traditional machine learning models on Databricks, emphasizing hands-on demonstrations and workflows using popular ML libraries

This course focuses on executing common tasks efficiently with AutoML and MLflow

Participants will delve into key topics, including regression and classification models, harnessing Databricks' capabilities to track model training, leveraging feature stores for model development, and implementing hyperparameter tuning

Additionally, the course covers AutoML for rapid and low-code model training, ensuring that participants gain practical, real-world skills for streamlined and effective machine-learning model development in the Databricks environment