The purpose of this individual assignment is to learn how to develop parallel machine learning (ML) applications in Amazon AWS cloud platform. Specifically, you will learn: (1) how to use Apache Spark to train an ML model in parallel on multiple EC2 instances; (2) how to use Spark's MLlib to develop and use an ML model in the cloud; (3) How to use Docker to create a container for your ML model to simplify model deployment. Description: You have to build a wine quality prediction ML model in Spark over AWS. The model must be trained in parallel using 4 EC2 instances. Then, you need to save and load the model in a Spark application that will perform wine quality prediction; this application will run on one EC2 instance. The assignment must be implemented in Java on Ubuntu Linux. The details of the assignment are presented below: • Input for model training: we share 2 datasets with you for your ML model. Both datasets are available in Canvas, under Programming Assignment 2. o TrainingDataset.csv: you will use this dataset to train the model in parallel on multiple EC2 instances. o ValidationDataset.csv: you