Add Intelligence to Applications with AWS ML Services

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Build Intelligent Applications with AWS ML Services
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A Long History of Machine Learning at Amazon
Personalized
recommendations
Inventing entirely
new customer
experiences
Fulfillment
automation and
inventory
management
Drones Voice driven
interactions

Put machine learning in the hands
of every developer and data scientist
Machine Learning at AWS
Our mission:

The Amazon machine learning stack
PLATFORM SERVICES
APPLICATION SERVICES
FRAMEWORKS & INTERFACES
Caffe2 CNTK Apache
MXNet PyTorch TensorFlow Torch Keras Gluon
AWSDeepLearningAMIs
AmazonSageMaker
Rekognition Transcribe Translate Polly Comprehend Lex
AWS
DeepLen
s
EDUCATIO N
The Amazon Machine Learning Stack
AmazonMechanical Turk

Bottom Layer: Frameworks & interfaces
NVIDIA
Tesla V100 GPUs
P3
AWS Deep Learning AMI
5,120 Tensor cores
128GB of memory
1 Petaflop of compute
NVLink 2.0
~14X faster than P2

Amazon SageMaker
Collect and prepare
training data
Choose and
optimize your ML
algorithm
Set up and manage
environments for
training
Train and tune model
(trial and error)
Deploy model
in production
Scale and manage
the production
environment
E a s i l y b u i l d , t r a i n , a n d d e p l o y m a c h i n e l e a r n i n g m o d e l s

Amazon SageMaker
P re-built
notebooks for
com m on
problem s
K -M e a n s C lu s te rin g
P rin c ip a l C o m p o n e n t A n a ly s is
N e u ra l T o p ic M o d e llin g
F a c to riz a tio n M a c h in e s
L in e a r L e a rn e r - R e g re s s io n
X G B o o s t
L a te n t D iric h le t A llo c a tio n
Im a g e C la s s ific a tio n
S e q 2 S e q
L in e a r L e a rn e r - C la s s ific a tio n
ALGORITHMS
Apache MXNet
TensorFlow
Caffe2, CNTK,
PyTorch, Torch
FRAMEWORKS S e t u p a n d m a n a g e
e n v i r o n m e n t s f o r
t r a i n i n g
T r a i n a n d t u n e
m o d e l ( t r i a l a n d
e r r o r )
D e p l o y m o d e l
i n p r o d u c t i o n
S c a l e a n d m a n a g e t h e
p r o d u c t i o n e n v i r o n m e n t
B uilt-in, high
perform ance
algorithm s
BUILD

Amazon SageMaker
P re-built
notebooks for
com m on
problem s
B uilt-in, high
perform ance
algorithm s
O ne-click
training
H yperparam eter
optim ization
BUILD TRAIN
Deploy model
in production
Scale and manage
the production
environment

Amazon SageMaker
Fully m anaged
hosting w ith auto-
scaling
O ne-click
deploym ent
P re-built
notebooks for
com m on
problem s
B uilt-in, high
perform ance
algorithm s
O ne-click
training
H yperparam eter
optim ization
BUILD TRAIN DEPLOY

Can we do more to put ML in the hands of
all developers (literally)?

AWS DeepLens
HDvideo camera
Custom-designed
deep learning
inference engine
Micro-SD
Mini-HDMI
USB
USB
Reset
Audio out
Power
H D video cam era
w ith on-board
com pute optim ized
for deep learning
Tutorials, exam ples,
dem os, and pre-built
m odels
From unboxing to
first inference in
<10 m inutes
Integrates w ith A m azon
S ageM aker and A W S
Lam bda
10
MIN

AWS Machine Learning Services for Computer Vision

Amazon Rekognition
Easy-to-use deep learning-based computer vision analysis
Fully
managed
service
Easy-to-use
API
Low costImage
analysis

Amazon Rekognition Image
Detect objects, scenes, and faces, extract text and identify unsafe content in images
Object and Scene
Detection
Facial
Analysis
Face
Recognition
Text in Image
Unsafe Image
Detection
Celebrity
Recognition
Face
Comparison

Demo
Rekognition Console

Demo
https://amzn.to/takeselfie

Demo
Rekognition API

Example: Serverless Image Processing Workflow
https://github.com/aws-samples/lambda-refarch-imagerecognition/

2. Submit
Image
4. DetectFaces 7. DetectText
1. Upload
3. Store image Lambda Step Functions
5.DetectLabels 6.DetectModerationLabels
8. Store Metadata
& analysis
DynamoDB
ElasticSearch
Analyze Images

Video Analysis
Limitations of traditional solutions
Temporal
information lost
Motion
context lost

Amazon Rekognition Video
Analyze activity, recognize, and track people in stored and live video
Facial
Analysis

Language and Speech Services

Common Language Use Cases
Information Bots
Education
Accessibility
Knowledge Management
Voice of Customer
Applications
Customer Service/
Call Centers
Enterprise
Digital Assistant
Semantic Search
Captioning Workflows
LocalizationPersonalization

Powerful speech and language capabilities
Amazon Transcribe Automatic conversion of speech into accurate, grammatically correct
text
Amazon Translate Natural and fluent language translation
Amazon Polly Turn text into lifelike speech using deep learning
Amazon Comprehend Discover insights and relationships in text
Amazon Lex Conversational interfaces for text-based and voice-based applications

Amazon Transcribe
Automatic conversion of speech into accurate, grammatically correct text
Support for
telephony
audio
Timestamp
generation
Intelligent
punctuation and
formatting
Recognize
multiple
speakers
Custom
vocabulary
Multiple
languages

Timestamping and Confidence Score
1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0
“Hi I would like to reschedule my flight to Seattle to later tonight”
3.480sec
Confidence: 1
6.402sec
Confidence: 0.95
10.541sec
Confidence: 1

Amazon Transcribe Demo

Amazon Translate
Natural and fluent language translation
Real-time
translation
Batch analysis Automatic language
recognition
Low cost

Amazon Translate Demo
• Translate a greeting
• Speak the greeting
• Add SSML for further control

Amazon Polly
Turn text into lifelike speech using deep learning
Wide selection of
voices and languages
Synchronize
speech
Fine-grained
control
Unlimited replay

Amazon Polly Demo
• Call Amazon Polly
• Save output locally as mp3 files

Demo: Translate a chat channel using Amazon Translate

Amazon Comprehend
Storm
World Series
Stock market
Washington
L i b r a r y o f n e w s
a r t i c l e s
Amazon
Comprehend
Discover insights and relationships in text using deep learning

Amazon Comprehend
Discover insights and relationships in text using deep learning
Entities
Key Phrases
Language
Sentiment
Amazon
Comprehend

© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved©2017, AmazonWebServices, 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 ma z o n . c o m: Or g a n i z a t i o n
– S e a t t l e , WA : 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
– Ou r c u s t o me 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

Amazon Comprehend Demo
• Download Amazon Video review data
• Use Amazon Comprehend
– detect sentiment
– identify key phrases

Amazon Lex
Building conversational interfaces into any application using voice and text
Integrated
development in
the AWS console
Trigger
Lambda
functions
Multi-step
conversations
One-click
deployment
Enterprise
connectors
Fully
managed

Demo
• Create an Amazon Lex chatbot for ordering coffee
• Call the chatbot

The broadest ML platform, that’s easiest to use, and has
the most customers
DATA LAKE STORAGE
Amazon S3
SECURITY
Access Control
Encryption
COMPUTE
Powerful GPU and CPU Instances
ANALYTICS
Amazon Athena
Amazon Redshift and Redshift Spectrum
Amazon EMR
(Spark, Hive, Presto, Pig)
AWS Glue
Amazon Kinesis
Amazon QuickSight
Amazon Macie
AWS Organizations
Complementary Services
APPLICATION SERVICES
Amazon Lex
Amazon Polly
Amazon Comprehend
Amazon Translate
Amazon Transcribe
Amazon Rekognition Image
Amazon Rekognition Video
PLATFORM SERVICES
Amazon SageMakerAWS DeepLens
FRAMEWORKS AND INTERFACES
AWS Deep Learning AMI
Apache MXNet
Caffe2
CNTK
PyTorch
TensorFlow
Theano
Torch
Gluon
Keras
AWS ML Platform AWS ML Customers

Try it yourself!
https://github.com/aws-samples/aws-ai-bootcamp-labs

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Add Intelligence to Applications with AWS ML Services

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