Learning Objectives: - How to use machine learning and NLP to find insights and relationships in text - How to use new pre-built models in Amazon Comprehend - How to create new models in Amazon SageMaker

1. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Pratap Ramamurthy
Partner Solutions Architect, AWS
How to enhance your
applications using Amazon
Comprehend for NLP

2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Voice-of-the-Customer Application

3. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Internal NLP
Transform Deliver
Gather customer feedback Process Categorize and Score Distill Actionable Insight and
make it accessible
• Email / Chat Transcripts
• Online Return Center
• Tickets
• Ad Hoc Sources
• Survey
External
• Social Media
• Forums
• Customer Reviews
Structured Data Joiner
Sentiment Scoring
Classification
Analysis Preparation
Analysis Database
Reports & Validation
Discovery & Exploration
Event Detection
Collect

4. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Serverless VOC Application

5. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Scenario: Wild Rydes (AWS Workshop)
The Wild Rydes Serverless Web Application Workshop introduces the
basics of building web applications using serverless infrastructure.

6. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Step 1: Static Website Hosting
OBJECTIVE: Create a bucket in Amazon S3 and configure it for static website
hosting. The static HTML, JS, and CSS will be served directly to user
browsers from Amazon S3.

7. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Step 2: User Management
OBJECTIVE: Allow visitors to register as a new user on Wild Rydes, by providing
and validating their email address. Amazon Cognito will be used to manage the
User Pool for Wild Rydes.

8. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Step 3: Serverless Service Backend
OBJECTIVE: Create a service backend using AWS Lambda and Amazon
DynamoDB to handle requests from your frontend static website content.

9. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Step 4: Create RESTful API
OBJECTIVE: Use API Gateway to expose the Lambda function you built in the
previous module as a RESTful API

10. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Serverless NLP application

11. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
NLP on AWS
Frameworks & Interfaces
AWS Deep Learning AMI
Vision Services:
Amazon Rekognition Image
Amazon Rekognition Video
Language Services:
Amazon Comprehend, Amazon Lex, Amazon Polly, Amazon
Translate, Amazon Transcribe
Apache
MXNet
Theano
Microsoft
Cognitive
Toolkit
Keras
Caffe2
& Caffe
TensorFlow Gluon
Application Services
Platform Services
Amazon SageMaker AWS DeepLens
PyTorch

12. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Serverless VOC architecture
API Gateway
Dynamo
Amazon
Comprehend
Amazon
Translate
Amazon
Sagemaker

13. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Sentiment analysis
I love my country.
positive sentiment negative sentiment
I hate the flu.

14. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Training NLP is Hard and Expensive
NLP Model
Data Collection
and Prep
Training the
model
Data annotation

15. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon Comprehend: NLP
😃
Sentiment Entities Languages Key phrases Topic modeling
POWERED BY DEEP
LEARNING

16. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
A m a z o n . c o m , I n c . i s l o c a t e d i n
S e a t t l e , W A a n d w a s f o u n d e d J u l y
5 t h , 1 9 9 4 b y J e f f B e z o s . O u r
c u s t o m e r s l o v e b u y i n g e v e r y t h i n g
f r o m b o o k s t o b l e n d e r s a t g r e a t
p r i c e s
N a m e d E n t i t i e s
• A m a z o n . c o m :
O r g a n i z a t i o n
• S e a t t l e , W A : L o c a t i o n
• J u l y 5 t h , 1 9 9 4 : D a t e
• J e f f B e z o s : P e r s o n
K e y p h r a s e s
• O u r c u s t o m e r s
• b o o k s
• b l e n d e r s
• g r e a t p r i c e s
S e n t i m e n t
• P o s i t i v e
L a n g u a g e
• E n g l i s h
Text Analysis

17. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Topic Modeling
Document Topic Proportion
Doc.txt 0 .89
Doc.txt 1 .67
Doc.txt 2 .91
Topic Term Weight
0 Washington .89
1 Silicon Valley .67
2 Roasting .91
Keywords Topic Groups Document Relationship to Topics

18. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Lambda code for Comprehend (python)
import boto3
import json
comprehend = boto3.client(service_name='comprehend',
region_name='us-east-1')
def lambda_handler(event, context):
text = format(event['review'])
jsonstr = json.dumps(comprehend.detect_sentiment(
(Text=text, LanguageCode='en'),
sort_keys=True, indent=4)
result = json.loads(jsonstr)
return result["Sentiment"]

19. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
In java…
AmazonComprehend client = AmazonComprehendClientBuilder.standard()
.withCredentials(new AWSStaticCredentialsProvider(awsCreds))
.withRegion("region")
.build();
String[] textList = {"I love Seattle", "Today is Sunday", "Tomorrow is Monday”};
// Call detectEntities API
BatchDetectEntitiesRequest batchDetectEntitiesRequest = new BatchDetectEntitiesRequest()
withTextList(textList)
withLanguageCode("en");
BatchDetectEntitiesResult batchDetectEntitiesResult =
client.batchDetectEntities(batchDetectEntitiesRequest);
for(BatchDetectEntitiesItemResult item : batchDetectEntitiesResult.getResultList())
{
System.out.println(item);
}

20. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Serverless VOC architecture
API Gateway
Amazon
Comprehend
Amazon
Comprehend
Amazon
Comprehend

21. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
End-to-End
Machine Learning
Platform
Zero setup Flexible Model
Training
Pay by the second
$
Amazon SageMaker
Build, train, and deploy machine learning models at scale

22. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
One-click training for
ML, DL, and custom
algorithms
Easier training with
hyperparameter
optimization
Highly-optimized
machine learning
algorithms
Deployment
without
engineering effort
Fully-managed
hosting at scale
BuildPre-built notebook
instances
Deploy
Train
Amazon SageMaker

23. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Data Visualization &
Analysis
Business Problem –
ML problem framing Data Collection
Data Integration
Data Preparation &
Cleaning
Feature Engineering
Model Training &
Parameter Tuning
Model Evaluation
Are Business
Goals met?
Model Deployment
Monitoring &
Debugging
– Predictions
YesNo
DataAugmentation
Feature
Augmentation
The Machine Learning Process
Re-training

24. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Serverless VOC architecture
API Gateway
Dynamo
Amazon
Comprehend
Amazon
Translate
Amazon
Sagemaker

25. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Cost estimate with Comprehend
Service Pricing Monthly estimate
Lambda 0.00001667 per GB second $16.67
API gateway $3.50 per million calls $3.500
S3 $0.0245 per GB $0.024
Comprehend $0.0001 PER UNIT $100.0
Dynamodb $0.47 per WCU
$0.09 per RCU
$0.25 per GB
$0.810
Total $121.0
( for 1 million sentences)

26. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Thank you!
Get started with Amazon Comprehend:
https://aws.amazon.com/comprehend