Accelerating-ML-Adoption-with-Our-New-AI-Services

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M IT
Accelerating ML adoption with our
new AI services
Simon Lee
Business Development Manager
AWS

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 ML
Services, you get quality and accuracy from continuously-
learning APIs with little to no data science experience

© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
2019
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 &
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
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
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 M A Z O N 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 )
A M A Z O N
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

Amazon Textract
Automatically extract text and data from scanned
documents and go beyond simple optical character
recognition (OCR) to also identify the contents of
fields in forms and information stored in tables.

Documents and forms can be complicated…
…not a single corresponding pixel value in common

Text extraction Table extraction Form extraction
Amazon Textract

Blocks: PAGE, PARAGRAPH, LINE, WORD
is washed by waves, and cooled
Amazon
Textract

Name Description
Blocks List of blocks identified
from the document
ID Unique ID of the unit
Relationships CHILD
Block type PAGE, PARAGRAPH, LINE, WORD
Pages Contains number of
pages in the document
Name Description
Document Blob or Amazon S3
object
Amazon
Textract

Name Description
object
FeatureTypes TABLES
Name Description
from the document
Relationships CHILD
Block type PAGE, TABLE, CELL
Amazon
Textract

Name Description
object
FeatureTypes FORMS
Name Description
from the document
Relationships KEY, VALUE, CHILD
Block type PAGE, KEY_VALUE_SET
Amazon
Textract

Input
Uploaded
documentimages
of invoices,be it
scannedor
photographed
AmazonS3
Uploaded
documentsare
stored in S3
AmazonAthena
Query blobs of data
on Amazon S3 data
lake
Amazon
Quicksight
Discoverinsights
and produce
forecaststo
improve services
AmazonTextract
Automatically
extract words and
lines of text, and
tables
AWS Lambda
Convert table data
into machine
readable format
AmazonS3
Store returned
information as flat
file on data lake

Amazon Forecast
Accurate time-series forecasting service, based
on the same technology used at Amazon.com.
No ML Experience Required

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

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

Amazon Forecast – Algorithms
Use AutoML or pick a
pre-defined algorithm
• Choose a pre-existing
algorithm or
• AutoML and Forecast will
pick the right recipe for
you
• ARIMA

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

• Amazon Forecast is applicable across
multiple domains
• You can set your domain using the
console or via the API
• You upload datasets with different
schemas based on the domain
Applicable across multiple domains

Key metrics reported by Amazon Forecast
Amazon Forecast creates probabilistic forecasts (i.e, forecasts for
specific prediction intervals)

Amazon Personalize
Batch or Real-time personalization and
recommendation service. No ML experience required.

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

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

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

Amazon Personalize: real-time data and batch data
ingestion
Historical user
activity
User
attributes
Item
catalog
Real-time data
Mobile
SDKs
JavaScript SDK
Amazon S3
bucket
Server-Side SDKs
Offline data
Amazon
Personalize

Demo
Web
Application
Browser /
Application
Real-time event data
Amazon
Personalize

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
The Amazon ML Stack: Broadest & Deepest Set of Capabilities
A I S E R V I C E S
Vision Speech 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 D E P L O Y
Pre-built algorithms & notebooks
Data labeling (G R O U N D T R U T H )
One-click model training & tuning
Optimization ( N E O )
One-click deployment & hosting
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
Models without training data (REINFORCEMENT LEARNING)Algorithms & models ( A W S M A R K E T P L A C E )
Language Forecasting Recommendations
NEW NEWNEW
NEW
NEW
NEWNEW
NEW
NEW
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 &
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
A M A Z O N
T E X T R A C T
A M A Z O N
P E R S O N A L I Z E
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 M A Z O N 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

Visit Booth 10 at the AWS Pavilion for
more on Real-Time Personalization
and Recommendation

Thank you!
Simon Lee
simonhl@amazon.com

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