You'll learn the importance of deep learning for artificial intelligence.

2. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Guy Ernest, Principal Solutions Architect, Amazon AI
October 10, 2017
Introduction to Deep
Learning on AWS with
TensorFlow

3. Why are we here?
Why Deep Learning?
Why Now?
Why Cloud?
Why Amazon?
Why You?
Why TensorFlow?
Why Keras?
Why Not a Demo?

4. Why are we here?
Why Deep Learning?

6. Neural Style Transfer

7. Neural Style Transfer

8. Neural Style Transfer

9. Neural Style Transfer

10. Why are we here?
Why Now?

11. Fast Compute
Ubiquitous Data
Advanced Learning Algorithms

12. Why are we here?
Why Cloud?

13. The circle of ML
Front-End team
Data Engineering team
Analysts / DS team
DevOps team
Business Problem
Data
ML Model
ML Application

14. The circle of ML
Front-End team
Data Engineering team
Analysts / DS team
DevOps team
Business Problem
Data
ML Model
ML Application
S3
EMR
Kinesis *
Redshift
Athena
Glue
ECS
Lambda
API-GW
Code *
DMS
EB
P2
Spot
Batch IoT
GreenGrass
FPGA
Edge
Snowball

15. AWS Snowball Edge
100T Data Transport Device
With On-board Compute

16. Security & Encryption Integrated Across The Platform
Fine grained
access controls
Broad KMS
integration
Server-side
encryption
with CMK
Audit key
usage by
user & role
Import
keys
Policy
validation
& simulation

17. Why are we here?
Why Amazon?

19. Artificial Intelligence At Amazon
Thousands Of Employees Across The Company Focused on AI
Discovery &
Search
Fulfilment &
Logistics
Enhance
Existing Products
Define New
Categories Of
Products
Bring Machine
Learning To All

23. • Applied Research
• Core Research
• Alexa
• Demand Forecasting
• Risk Analytics
• Search
• Recommendations
• AI Services | Rek, Lex, Polly
• Q&A Systems
• Supply Chain Optimization
• Advertising
• Machine Translation
• Video Content Analysis
• Robotics
• Lots of Computer Vision..
• NLP / NLU
Just a few Deep Learning Use Cases at Amazon…

24. Running AI In Production on AWS Today

25. Pinterest
Visual Search

26. Pinterest Lens

28. Recommendations & Ranking At Netflix
Personalized ranking,
page generation,
search, similarity, ratings
In 140 new countries,
simultaneously

29. Why are we here?
Why You?

30. Amazon AI
Intelligent Services Powered By Deep Learning

31. More in
2017
Infrastructure CPU
Engines MXNet TensorFlow Caffe Theano Pytorch CNTK
Services
Amazon Polly
Platforms
IoT
Speech
Mobile
Amazon
ML
Spark &
EMR
Kinesis Batch ECS
GPU
More in
2017
Chat
Amazon Lex
Amazon AI: Machine Learning In The Hands Of Every Developer
Amazon Rekognition
Vision

32. More in
2017
Infrastructure CPU
Engines MXNet TensorFlow Caffe Theano Pytorch CNTK
Services
Amazon Polly
Platforms
IoT
Speech
Mobile
Amazon
ML
Spark &
EMR
Kinesis Batch ECS
GPU
More in
2017
Chat
Amazon Lex
Amazon AI: Machine Learning In The Hands Of Every Developer
Amazon Rekognition
Vision

33. Why are we here?
Why TensorFlow?

34. TensorFlow Execution Engine
Python Frontend
Deep Learning Layers
Keras API
Canned Estimators
TensorFlow Layers
with tf.Session() as sess:
sess.run(init)
sess.run(optimizer)
tf.layers.dense(…)
tf.layers.conv2d(…)

35. TensorFlow Execution Engine
Execution
Graph

36. Why are we here?
Why Keras?

37. TensorFlow Execution
Engine
Python Frontend
Deep Learning Layers
Keras API
Canned Estimators
Keras Example
from keras.models import Sequential
model = Sequential()
from keras.layers import Dense, Activation
model.add(Dense(units=64, input_dim=100))
model.add(Activation('relu'))
model.add(Dense(units=10))
model.add(Activation('softmax'))
model.compile(loss='categorical_crossentropy',
optimizer='sgd', metrics=['accuracy'])
model.fit(x_train, y_train, epochs=5, batch_size=32)

38. “Sounds great!
How can we get started?”

39. Code Walkthrough
MNIST (Hello World) with Keras on Tensorflow

40. AWS Deep Learning AMI: One-Click GPU Deep Learning
Up To 40,000
CUDA Cores
Python 3 Notebooks
& Examples
(and others)(Volta at launch)
Scale for
Training
TensorFlow,
Apache MXNet

41. Learn more:
AWS Deep Learning AMIs: https://aws.amazon.com/amazon-ai/amis/
TensorFlow on AWS: https://aws.amazon.com/tensorflow/

42. Thank You!