# SageMaker + EMR: MLlib model training & Hosting on SageMaker

In this lab, we're going to utilize our knowledge of connecting and interacting with EMR clusters in order to train a 
model using Spark MLlib. We'll serialize this model and then host it on SageMaker. 

MLlib is Spark’s machine learning (ML) library. At a high level, it provides tools such as:

* ML Algorithms: common learning algorithms such as classification, regression, clustering, and collaborative filtering
* Featurization: feature extraction, transformation, dimensionality reduction, and selection
* Pipelines: tools for constructing, evaluating, and tuning ML Pipelines
* Persistence: saving and load algorithms, models, and Pipelines
* Utilities: linear algebra, statistics, data handling, etc.