Building Intelligent Applications (No Machine Learning Experience Required!)

P U B L I C S E C T O R
S U M M I T
WASHINGTON, D C

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C T O R
S U M M I T
Building Intelligent Applications
(No Machine Learning Experience Required!)
Ben Snively
Principal Solutions Architect
Amazon Web Services
2 9 6 6 9 7

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
S U M M I T
Agenda
Intelligent applications in the public sector (built without being
a Data Scientist)
Amazon Artificial Intelligence services
Architectures deep dives
Demonstrations interleaved throughout
Next step/Call to action

S U M M I T
Intelligent Applications in Public Sector

S U M M I T
AWS artificial intelligence services create better customer
experiences, improve agent efficiency, and surface meaningful
insights for contact center managers and supervisors.
Understanding your citizens, contributors, students, or other
stakeholders is easier today than ever before. Natural language
capabilities can capture a wealth of information, such as
sentiment and conversational intent.

S U M M I T
AWS artificial intelligence services create better student
environments, improve student outcomes, improve faculty,
predict course utilization, and many other use cases.

S U M M I T
Customer Success In Education
Amazon Transcribe used to offer
effective and affordable closed
captioning for academic video

S U M M I T
Patient and population
health analytics
Personalized medicine
Clinical trial
managementRevenue cycle
management (Medical
Coding)
Pharmacovigilance
PHI Compliance
Predictive medicine

S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
S U M M I T
Identifying critical
medical forms
Beth Israel Deaconess Medical Center uses
Amazon Comprehend Medical to identify
completed history and physical forms before a
surgery, lowering the number of delayed or
cancelled procedures.

S U M M I T
Collect Store Enrich Deliver
GB to Petabytes of
documents, images,
and video assets
Centralized
storage
and global
registry
Metadata enrichment
through machine
learning and deep
learning
Enhanced value
and search
experience
Right
content to
the right
users

S U M M I T
Identifying fraudulent
financial transactions
Identity theft
detection
Large scale fraud
investigations
Credit Risk Prediction

S U M M I T
of storageevents per day
30+pb135 Billion
Up to
Monitoring 99% equities
& 65% options in the U.S.
Reconstructing
Trillions
of market nodes & rdges
Investor
protection
Market
integrity

S U M M I T
FINRA Challenge: Unstructured Data
• High volumes of unstructured content
• ~1M documents each year from stock brokers and investors
to be reviewed
• Documents contain incredibly useful information but
mining is a challenge
• Complex cases might have 1000s of
associated records
• Numerous features of interest
• Finding information about the who, what, where, when,
and how is labor intensive
Documents
Reference Data
Forms
Free Style Text
S U M M I T

S U M M I T
Amazon AI Services
Easily integrate with your applications to address common
use cases such as time series forecasting, document
analysis, personalized recommendations, and others.
Because we use the same deep learning technology that
powers Amazon.com and our Machine Learning (ML)
Services, you get quality and accuracy from continuously
learning APIs with little to no data science experience

S U M M I T
M L F R A M E W O R K S &
I N F R A S T R U C T U R E
A I S E R V I C E S
A M A Z O N
R E K O G N I T I O N
I M A G E
A M A Z O N
P O L L Y
A M A Z O N
T R A N S C R I B E
A M A Z O N
T R A N S L A T E
A M A Z O N
C O M P R E H E N D &
C O M P R E H E N D
M E D I C A L
A M A Z O N
L E X
A M A Z O N
V I D E O
Vision Speech Language Chatbots
A M A Z O N
S A G E M A K E R
B U I L D T R A I N
A M A Z O N
F O R E C A S T
Forecasting
A M A Z O N
T E X T R A C T
Recommendations
D E P L O Y
Pre-built algorithms
Data labeling (G R O U N D T R U T H )
One-click model training & tuning
Optimization (N E O )
M L S E R V I C E S
F r a m e w o r k s I n t e r f a c e s I n f r a s t r u c t u r e
E L A S T I C
C O M P U T E
C L O U D
( A M A Z O N E C 2 )
P 3 & P 3 d n
A M A Z O N E C 2
C 5
F P G A s A W S I o T G R E E N G R A S S A M A Z O N
E L A S T I C
I N F E R E N C E
Reinforcement learning
Algorithms & models ( A W S M A R K E T P L A C E
F O R M A C H I N E L E A R N I N G )
I N F E R E N T I A
Notebook Hosting
One-click deployment & hosting
Auto-scaling
Virtual Private Cloud
Private Link
Elastic Inference integration
Hyper Parameter Optimization
A M A Z O N
P E R S O N A L I Z E

S U M M I T
A I S E R V I C E S
A M A Z O N
I M A G E
A M A Z O N
P O L L Y
A M A Z O N
T R A N S C R I B E
A M A Z O N
T R A N S L A T E
A M A Z O N
C O M P R E H E N D
M E D I C A L
A M A Z O N
L E X
A M A Z O N
V I D E O
A M A Z O N
F O R E C A S T
Forecasting
A M A Z O N
T E X T R A C T
Recommendations
A M A Z O N

S U M M I T

S U M M I T
Contact Center Insights Architecture
Contact Trace
Record (CTR)
Recorded Call
Start Job
Is Job Done?
NLP
Insights and
Dashboards
upsert
Amazon Connect

S U M M I T
Ingesting and Enriching Scanned Content
Input
Uploaded document
images of notes,
explanation of benefits,
and forms
Amazon Simple
Storage Service
(Amazon S3)
Uploaded documents
are stored in S3
Amazon
Comprehend
Use natural language
processing to extract
insights from
documents
Amazon
Elasticsearch
Service
Easily search through
extracted data and text
insights
Output
Discover insights to
improve services
Amazon Textract
Automatically extract
words, lines of text,
and tables

S U M M I T

S U M M I T
Text extraction Table extraction Form extraction
Amazon Textract

S U M M I T
Amazon Comprehend
Entities
Key Phrases
Language
Sentiment
Syntax
Grouping
English, Spanish, German, French, Italian, Portuguese
Amazon
Comprehend

S U M M I T
Amazon Comprehend Medical
Extract text and data from virtually any document
K E Y F E A T U R E S
Medical
conditions
Anatomy
entities
PHI
identification
Medication and
dosage extraction
No ML experience
required

S U M M I T
• Lipitor: Brand Name
• 20 mg: Dosage
• Once Daily: Frequency
M r . S m i t h i s a 6 3 - y e a r - o l d
g e n t l e m a n w i t h c o r o n a r y
a r t e r y d i s e a s e a n d
h y p e r t e n s i o n . C U R R E N T
M E D I C A T I O N S : t a k i n g a d o s e
o f L I P I T O R 2 0 m g o n c e d a i l y
• Mr. Smith: Name
• 63 : Age
• Coronary artery : System Organ Site
• Coronary artery disease: Diagnosis Name
• Hypertension: Diagnosis Name
Relationship
extraction

S U M M I T
Predicts spikes
accurately!
Generates forecasts
for new items
Learns relationships
between multiple
related time-series
Incorporates external
data (holidays,
promotions, and
so on)
Amazon Forecast Solves Hard Problems in Forecasting

S U M M I T
Historical data
Sales, inventory, pricing, etc.
Related data
Weather, competitive promotions, etc.
1. Load data
2. Inspect data
3. Identify features
4. Select algorithms
5. Select hyperparameters
6. Train models
7. Optimize models
8. Deploy and host models
Amazon Forecast
Customized
Forecasting
API
Private
Amazon Forecast - How it Works

S U M M I T
There are three types of datasets in Amazon Forecast:
Item metadataTarget time-series Related time-series
Related time-
series such as
price, web-hits,
etc.
Historic time-
series data of
items to
forecast
Attributes of
the item such
as category,
genre, and
brand
Amazon Forecast Data Ingestions

S U M M I T
Amazon Forecast – Algorithms
Use AutoML or pick a
pre-defined algorithm
• Choose a pre-existing
algorithm (packaged as
Personalize Recipes)
• AutoML and Forecast will
pick the right recipe for
you
• ARIMA

S U M M I T
Real-time Works with almost any
product or content
K E Y F E AT U R E S
Responsive to changes
in intent
Automated
machine learning
Bring existing algorithms
from Amazon SageMaker
Deliver high quality
recommendations
Deep learning
enabled algorithms
Easy to Use

S U M M I T
Activity stream
Views, signups, conversion, etc.
Inventory
Videos, products, articles, etc.
Customized
Personalization
APIDemographics (optional)
Name, age, location, etc.
1. Load data
2. Inspect data
3. Identify features
4. Select algorithms
5. Select hyperparameters
6. Train models
7. Optimize models
8. Build feature store
9. Deploy and host models
10.Create real-time caches
Amazon Personalize
Amazon Personalize – How it Works

S U M M I T
Amazon Personalize – Algorithms
Use AutoML or pick a
pre-defined algorithm
• Picking an algorithm:
• Choose a pre-existing
algorithm (packaged as
Personalize Recipes)
• AutoML and Personalize will
pick the right recipe for
• Factorization machine
using a deep autoencoder
• Hierarchical recurrent
neural network

S U M M I T
Amazon Personalize: Real-Time Data and Batch Data
Ingestion
Historical user
activity
User
attributes
Item
catalog
Real-time data
Mobile
SDKs
(coming soon)
JavaScript SDK
Amazon S3
bucket
Server-Side SDKs
Offline data
Amazon
Personalize

S U M M I T
M L F R A M E W O R K S &
I N F R A S T R U C T U R E
A I S E R V I C E S
A M A Z O N
I M A G E
A M A Z O N
P O L L Y
A M A Z O N
T R A N S C R I B E
A M A Z O N
T R A N S L A T E
A M A Z O N
C O M P R E H E N D
M E D I C A L
A M A Z O N
L E X
A M A Z O N
V I D E O
A M A Z O N
S A G E M A K E R
B U I L D T R A I N
A M A Z O N
F O R E C A S T
Forecasting
A M A Z O N
T E X T R A C T
Recommendations
D E P L O Y
Pre-built algorithms
Data labeling (G R O U N D T R U T H )
One-click model training & tuning
Optimization (N E O )
M L S E R V I C E S
F r a m e w o r k s I n t e r f a c e s I n f r a s t r u c t u r e
E C 2 P 3
& P 3 d n
E C 2 C 5 F P G A s G R E E N G R A S S E L A S T I C
I N F E R E N C E
Reinforcement learning
Algorithms & models ( A W S M A R K E T P L A C E
F O R M A C H I N E L E A R N I N G )
I N F E R E N T I A
Notebook Hosting
One-click deployment & hosting
Auto-scaling
Virtual Private Cloud
Private Link
Elastic Inference integration
Hyper Parameter Optimization
A M A Z O N

S U M M I T
• Practical education on ML for new and experienced practitioners
• Based on the same material used to train Amazon developers
• A variety of learning paths from Developer to Data Scientist
https://aws.amazon.com/training/course-descriptions/machine-learning/
https://aws.amazon.com/training/course-descriptions/deep-learning/
ML Training
AWS Machine Learning University

S U M M I T
MLSolutionsLab
Brainstorming
Custom modeling
Training
Work side-by-side with AWS experts
https://aws.amazon.com/ml-solutions-lab/
How we can help…

S U M M I T
ml.aws

Thank you!
S U M M I T

Building Intelligent Applications (No Machine Learning Experience Required!)

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