## Data Preparation using Amazon SageMaker and Glue DataBrew

This project contains the code for the [Workshop](https://catalog.us-east-1.prod.workshops.aws/v2/workshops/1e224d5a-4273-444a-acec-28d44a5bfb28)

### About the Workshop
The workshop will cover various data preparation and feature engineering options available with AWS services like SageMaker Processing, Data Wrangler and Glue DataBrew to perform encoding, transformations and visualization.

Data Wrangler makes it easy to work interactively on data preparation steps before transforming them into code that can be used immediately for ML model experimentation and into production.
With SageMaker Processing, you can use a simplified, managed experience on SageMaker to run your data processing workloads, such as feature engineering, data validation, model evaluation, and model interpretation.
AWS Glue DataBrew is a new visual data preparation tool that makes it easy for data analysts and data scientists to clean and normalize data to prepare it for analytics and machine learning.
Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, update, retrieve, and share machine learning (ML) features. Finally we use the processed dataset and Feature Store to training and deploying an XGBoost model as a sample

### Security

See [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.

### License

This library is licensed under the MIT-0 License. See the LICENSE file.