# SageMaker + EMR: Deep Learning Regression

In this lab, we're going to utilize our knowledge of connecting and interacting with EMR clusters in order to perform
dataprep at scale for a custom deep learning model we wish to produce. We'll use the Studio interface to:
1. Perform scalable data prep on EMR using PySpark
2. Prototype models and data loaders using Studio Notebook's built in TensorFlow kernels
3. Scale our training using SageMaker Training and log experiment which we'll review in Studio