A look at the deep lens from AWS and a fun demo with hard hats!

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Ric Harvey, Senior Technical Evangelist
AWS DeepLens:
A New Way to Learn Machine Learning

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AWS DEEPLENS
IS NOT A
VIDEO CAMERA…
…IT’S THE
WORLDS FIRST
DEEP LEARNING
ENABLED
DEVELOPER KIT

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PLATFORM SERVICES
APPLICATION SERVICES
FRAMEWORKS & INTERFACES
Caffe2 CNTK
Apache
MXNet
PyTorch TensorFlow Chainer Keras Gluon
AWS Deep Learning AMIs
Amazon SageMaker
Rekognition Transcribe Translate Polly Comprehend Lex
AWS
DeepLens
EDUCATION
THE AMAZON MACHINE LEARNING STACK

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GET STARTED WITH SAMPLE PROJECTS
ARTISTIC STYLE
TRANSFER
OBJECT
DETECTION
FACE DETECTION /
RECOGNITION
HOT DOG / NOT
HOT DOG
CAT VS. DOG
ACTIVITY
DETECTION
A D D C U S T O M F U C T I O N A L I T Y
O R
C R E A T E YO UR O W N P R O J E C T I N A M A Z O N S A G E M A K E R

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2. DEEPLENS
OVERVIEW
1. MACHINE LEARNING
OVERVIEW
TODAY WE WILL COVER
3. Demo Time

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1. MACHINE LEARNING
OVERVIEW

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Model training Inference
OVERVIEW OF DEEP LEARNING
Data

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DATA
Annotate Preprocess Data split

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MODEL TRAINING
• Define model architecture
• Input the annotated and cleaned data into the model
• Multiple iterations (epochs) to train the model
• Validate with held back dataset
Large,
annotated
dataset
Training set
Validation set
Training
Validate

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INFERENCE
It’s where the magic happens!
1. Preprocess new data/image just like training set.
2. Feed image back to the trained model to get a predicted output.

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2. DEEPLENS OVERVIEW

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DEEPLENS SPECIFICATIONS
• Intel Atom Processor
• Gen9 graphics
• Ubuntu OS- 16.04 LTS
• 100 GFLOPS performance
• Dual band Wi-Fi
• 8 GB RAM
• 16 GB Storage (eMMC)
• 32 GB SD card
• 4 MP camera with MJPEG
• H.264 encoding at 1080p resolution
• 2 USB ports
• Micro HDMI
• Audio out
• AWS Greengrass preconfigured
• clDNN Optimized for MXNet

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UNDER THE COVERS - CONSOLE

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UNDER THE COVERS – DEVICE

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AWS DEEPLENS ARCHITECTURE
Video out
Data out
I N F E R E N C E
D E P L O Y P R O J E C T S
Manage device
Security
Console Project
Management
AWS Cloud
Intel: Model Optimizer
cIDNN and Driver

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Demo Time
https://github.com/jennyd77/WorkSiteSafety