Summit Milano 2019 - Rendi le tue app più smart con i servizi AI di AWS- Julien Simon, Principal Evangelist ML AI, AWS

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Make your apps smarter with AWS AI services
Julien Simon
Global Evangelist, AI & Machine Learning
@julsimon

2. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Centerpiece for digital transformation
Customer
experience
Business
operations
Decision
making
Innovation Competitive
advantage
of digital transformation initiatives
supported by AI in 201940%

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Our mission at AWS
Put machine learning in the hands
of every developer

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Our Approach for Machine Learning
Customer-focused
90%+ of our ML roadmap is
defined by customers
Multi-framework
Support for the most
popular frameworks
Pace of innovation
200+ new ML launches and major feature
updates in the last year
Breadth and depth
A wide range of AI and ML services in-
production
Security and analytics
Deep set of security and
encryption features, with robust analytics
capabilities
Embedded R&D
Customer-centric approach to
advancing the state of the art

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More machine learning happens on AWS than anywhere else

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© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark
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
R E K O G N I T I O N
I M A G E
P O L L Y T R A N S C R I B E T R A N S L A T E 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
L E XR E K O G N I T I O N
V I D E O
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
F O R E C A S TT E X T R A C T P E R S O N A L I Z E
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
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
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

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Put AI to work for your business
Pre-trained AI services that require
no ML skills or training
Easily add intelligence to your existing
apps and workflows
Quality and accuracy from
continuously-learning APIs
A I S E R V I C E S
R E K O G N I T I O N
I M A G E
P O L L Y T R A N S C R I B E T R A N S L A T E 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
L E XR E K O G N I T I O N
V I D E O
Vision Speech Chatbots
F O R E C A S TT E X T R A C T P E R S O N A L I Z E
Language Forecasting Recommendations

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Easily add intelligent image and video analysis to your applications.

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Amazon Rekognition:
Deep Learning-Based Image and Video Analysis

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Amazon Rekognition Benefits
Low cost
Your data
is your ownServerless
Rapid
integration
State of the
art capabilities
Continuous
improvement

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Aella Credit uses Amazon Rekognition to
analyze images to verify an individual’s identity in real-
time without human intervention, allowing it to provide
instant loans to eligible customers through its mobile
app.
Real-time identity verification
https://aws.amazon.com/blogs/machine-learning/aella-credit-empowers-
underbanked-individuals-by-using-amazon-rekognition-for-identity-verification/

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OCR++ service to easily extract text and data from
virtually any document. No ML experience required.

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Amazon Textract Features
Text extraction Table extraction Form extraction
# One line of code!
response = client.analyze_document(
Document={'S3Object': {'Bucket': bucket, 'Name': document}},
FeatureTypes=["TABLES", "FORMS"]
)

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Amazon Textract
Benefits

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« With Amazon Textract, we can automatically capture and validate data
from documents and forms, such as loan applications or vehicle titles, so
decisions can be made more quickly. This will reduce customer effort and
further streamline the process for everyone involved from the manufacturer
to the buyer. »
Bryan Landerman, Chief Technology Officer - Cox Automotive
Document & form processing

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17. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Accurate time-series forecasting service, based
on the same technology used at Amazon.com.
No ML experience required.

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Sample use cases
Product demand Workforce demand Financial
metrics
Inventory
planning

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Traditional time-series models

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Traditional time-series models
Trend + Seasonality

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Real-world time-series are often more complex

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Additional inputs are needed to predict accurately

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Traditional methods struggle with real-world series
Don’t consider
metadata
Don’t consider
external factors such
as holidays and
promotions
Can’t handle
time-series with
no history

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Using deep learning increases forecast accuracy
cold
start promotional spikes

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Amazon Forecast
Improve forecasting accuracy by up to 50% at 1/10th the cost
K E Y F E A T U R E S
Consider multiple
time-series
at once
Automatic
machine
learning
Visualize forecasts
& import results
into business apps
Evaluate model
accuracy
Schedule forecasts
and model
retraining
Bring existing
algorithms from
Amazon
SageMaker
Privacy
& encryption

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Amazon Forecast: How it works
Amazon Forecast

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Train models on your own data
Use AutoML or pick a
predefined algorithm
recipes AutoML
Hyper
Parameter Optimization
custom

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Probabilistic forecasts
Amazon Forecast creates probabilistic forecasts (that is, forecasts for
specific prediction intervals)

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« We have been using Amazon Forecast to predict demand for over 50,000
different products, using Amazon Forecast’s state-of-the-art deep learning
algorithms that we can use right out of the box.
Amazon Forecast takes care of all the heavy lifting of setting up pipelines,
re-training schedules, and re-generating forecasts, so we can experiment
with hundreds of models very easily. »
Fernando Croceri, Head of Analytics at Mercado Libre
Demand prediction at scale

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Real-time personalization and recommendation service,
based on the same technology used at Amazon.com.
No ML experience required.

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Common applications & use cases
Personalized
recommendations
Search
reranking
Notifications and
emailsRelated Items

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Personalizing user experience is proven to increase discoverability,
engagement, user satisfaction, and revenue
30% of page views on
Amazon are from
recommendations

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Effective personalization requires solving multiple hard problems
Reacting to user interactions in real time
Avoiding mostly showing popular items
Handling cold start (insufficient data about
new users/items)
Scale

35. Deep learning techniques have a direct impact on the bottom line
SimilarityPopularity
Neural
network
Matrix
factorization
+15.4%
Engagement Recurrent Neural
Net + Bandit
Rule-based card
ranker
Bayesian network
model
+7.4%
Engagement+29%
Click Through
+20%
Click Through

36. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Amazon Personalize
Improve customer experiences with personalization and recommendations
K E Y F E A T U R E S
Context-aware
Recommendations
Automated
machine learning
Bring existing algorithms
from Amazon SageMaker
Continuous learning
to improve
performance

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Amazon Personalize: How it works
Amazon Personalize

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Feeding data to Amazon Personalize
Historical user
activity
User
attributes
Item
catalog
Real-time data
Mobile
SDKs
(coming soon)
JavaScript SDK
Amazon S3
bucket
Server-Side SDKs
Offline data

39. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Train models on your own data
Use AutoML or pick a
predefined algorithm
recipes AutoML
Hyper
Parameter Optimization
custom

40. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
Domino’s uses Amazon Personalize to customize and
scale relevant marketing communications to customers
based on time, context, and content, thereby improving
and enhancing their experience with the Domino’s brand.
Personalizing customer experiences

41. S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.

42. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark
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
R E K O G N I T I O N
I M A G E
P O L L Y T R A N S C R I B E T R A N S L A T E 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
L E XR E K O G N I T I O N
V I D E O
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
F O R E C A S TT E X T R A C T P E R S O N A L I Z E
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
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
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

43. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
ml.aws
aws.training/machinelearning
https://aws.amazon.com/blogs/aws/amazon-forecast-time-series-forecasting-made-easy/
https://aws.amazon.com/blogs/aws/amazon-personalize-real-time-personalization-and-recommendation-for-everyone/

44. Thank you!
S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Julien Simon
Global Evangelist, AI and Machine Learning
@julsimon
https://medium.com/julsimon