From the course: Microsoft Azure Data Scientist Associate (DP-100) Exam Tips

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Training, managing, and deploying models in Azure Databricks

Training, managing, and deploying models in Azure Databricks - Azure Tutorial

From the course: Microsoft Azure Data Scientist Associate (DP-100) Exam Tips

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Training, managing, and deploying models in Azure Databricks

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- [Instructor] Azure Databricks supports several libraries for machine learning. There's one key library which has two approaches that are native to Apache Spark, MLlib and Spark ML. Read on in Microsoft Learn to learn more about these. The process of training and validating a machine learning model has three steps. First, you split the data, then you train a model, and lastly, you validate the model. Go over the Train a Machine Learning Model exercise to learn how to train a machine learning model with Azure Databricks.

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