Merge pull request aws#44 from awslabs/xgboost-updates

adding notebooks for data conversion and encryption

Author: vrkhare

advanced_functionality/README.md

@@ -8,3 +8,6 @@ Example Notebooks include:
 - *kmeans_bring_your_own_model*: How to use Amazon SageMaker Algorithms containers to bring a pre-trained model to a realtime hosted endpoint without ever needing to think about REST APIs.
 - *r_bring_your_own*: How to containerize an R algorithm using Docker and plumber for hosting so that it can be used in Amazon SageMaker's managed training and realtime hosting.
 - *xgboost_bring_your_own_model*: How to use Amazon SageMaker Algorithms containers to bring a pre-trained model to a realtime hosted endpoint without ever needing to think about REST APIs.
+- *handling_kms_encrypted_data.ipynb*: How to use Server Side KMS encrypted data with Amazon SageMaker training works. The IAM role used for S3 access needs to have permissions to encrypt and decrypt data with the KMS key.
+- *parquet_to_recordio_protobuf.ipynb*: How to convert Parquet data format into the recordIO-protobuf format that many SageMaker algorithms consume. 
+- *working_with_redshift_data.ipynb*: Demonstrates how to copy data from Redshift to S3 and vice-versa.