The document discusses building machine learning solutions on data lakes. It provides an agenda that includes loading data into Amazon DynamoDB and Amazon Kinesis, processing data with AWS Glue, and building models with Amazon SageMaker. Labs are described for each step that provide hands-on exercises for loading, streaming, processing and analyzing data to build recommendations models.

2. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Build Machine Learning Solutions
on Data Lakes
Vikrant Kahlir
Solutions Architect
AWS
A R C 3 2 1
Joseph Glover
Solutions Architect
AWS
Gitansh Chadha
Solutions Architect
AWS

3. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Agenda
Overview
Lab 1: Load data in Amazon DynamoDB
Lab 2: Amazon Kinesis
Lab 3: AWS Glue
Lab 4: Amazon SageMaker

4. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

5. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Build machine learning solutions on data lakes
Real-time ratings
Processed
data

6. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Link to workshop
https://bit.ly/2DOW6FB

7. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

8. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Build machine learning solutions on data lakes
Real-time ratings
Processed
data
Lab 1

9. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
AWS Database Migration Service (AWS DMS)
How it works
Load table by table
Creates tables at target database
Sets up metadata required at target
Populates data from source
Each process loads one entire table
Can use multiple processes
Can be paused
When restarted will continue from where
it was stopped
Will reload any tables that were currently
in progress
Replication
instance
Source Target

10. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Amazon DynamoDB
Table creation options
PartitionKey, Type:
SortKey, Type:
Provisioned Reads:
Provisioned Writes:
LSI Schema GSI Schema
AttributeName [S,N,B]
AttributeName [S,N,B]
1+
1+
Provisioned Reads: 1+
Provisioned Writes: 1+
TableName
Optional
Required
CreateTable
String,
Number,
Binary ONLY
Per Second
Unique to
Account and
Region
Highly available
Consistent, single-digit
millisecond latency
at any scale
Fully managed
Integrates with AWS Lambda,
Amazon Redshift, and more
Secure

11. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

12. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Build machine learning solutions on data lakes
Real-time ratings
Processed
data
Lab 2

13. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Streaming with Amazon Kinesis
Easily collect, process, and analyze video and data streams in real time
Capture, process, and
store video streams
Capture, process,
and store data
streams
Load data streams
into data stores
Analyze data streams
with SQL

14. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

15. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Build machine learning solutions on data lakes
Real-time ratings
Processed
data
Lab 3

16. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
AWS Glue
AWS Glue Data Catalog
Discover and organize your data in various databases, data
warehouses, and data lakes
Job authoring
Focus on the writing transformations
Generate code through a wizard, or write your own
Job execution
Runs jobs in Spark containers—automatic scaling
Fully managed hosting with auto scaling
AWS Glue is serverless—only pay for the resources you consume

17. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.

18. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Build machine learning solutions on data lakes
Real-time ratings
Processed
data
Lab 4

19. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Overview: Lab 4
Data exploration and preparation
One hot encoding
Binary recommender
Training and hosting
Factorization machines
Hyperparameters
Movie recommender
Nearest neighbor
Inference call

20. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Amazon SageMaker
Build
Pre-built Jupyter Notebooks
Built-in, high-performance algorithms
Train & tune
One-click training
Hyperparameter optimization
Deploy
One-click deployment
Fully managed hosting with auto scaling

21. Thank you!
© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Vikrant Kahlir
awsvik@amazon.com
Joseph Glover
joglover@amazon.com
Gitansh Chadha
gitanshc@amazon.com

22. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.