Transformers, Estimators, and Pipelines (3/5)

Unlock the full self-paced class from Databricks Academy! Introduction to Data Science and Machine Learning (AWS Databricks) https://academy.databricks.com/course/SP860 Introduction to Data Science and Machine Learning (Azure Databricks) https://academy.databricks.com/course/SP860-Az There are three main abstractions in Apache Spark’s Machine Learning Library: Transformers, Estimators, and Pipelines. In this video, Conor discusses the transform and fit methods implemented in Transformers and Pipelines, respectively, and how they are used to construct a full machine learning Pipeline. Conor then walks through the implementation of such a pipeline using Spark in Databricks. Download the code here: https://files.training.databricks.com/classes/ml/ml-on-spark.dbc Don't have a Databricks Account? Sign up for Community Edition: https://databricks.com/try-databricks This is Part 3 of our Introduction to Machine Learning Video Series: https://www.youtube.com/playlist?list=PLroeQp1c-t3pT3_d6JmjVnBdOKpyeQtQr