Introduction
Training and evaluating machine learning models is an iterative process that can require experimentation to identify the best combination of training algorithm and hyperparameter values for your data.
Azure Databricks has an AutoML feature that automates the process of training and validating models using different algorithms and hyperparameters. AutoML significantly reduces the effort needed to run and track model training experiments.
This module describes how to use AutoML in Azure Databricks to automate model training so you can reduce the effort required to create effective machine learning solutions.