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Brad Kenstler - A new way to learn machine learning.pdf

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In this session you will get to see AWS DeepLens in action! You will learn how AWS DeepLens empowers developers of all skill levels to get started with deep learning in less than 10 minutes by providing sample projects with practical, hands-on examples which can start running with a single click. In this session you will get an overview of how to build and deploy computer vision models, such as face detection using Amazon SageMaker and AWS DeepLens and learn about some of the great use cases that bring together multiple AWS services to create new to the world deep-learning enabled innovation.

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Brad Kenstler - A new way to learn machine learning.pdf

  1. 1. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Brad Kenstler AWS DeepLens: A New Way to Learn Machine Learning Data Scientist II
  2. 2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Fulfilment & Logistics Search & Discovery Existing Products New Products Thousands of Amazon Engineers Focused on AI
  3. 3. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Artificial Intelligence at Amazon
  4. 4. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. AWS DEEPLENS IS NOT A VIDEO CAMERA… …IT’S THE WORLDS FIRST DEEP LEARNING ENABLED DEVELOPER KIT
  5. 5. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. GET STARTED WITH SAMPLE PROJECTS ARTISTIC STYLE TRANSFER OBJECT DETECTION FACE DETECTION / RECOGNITION HOT DOG / NOT HOT DOG CAT VS. DOG ACTIVITY DETECTION ADD CUSTOM FUCTIONALITY OR CREATE YOUR OWN PROJECT
  6. 6. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 2. DEEPLENS OVERVIEW 1. MACHINE LEARNING OVERVIEW 4. EXTENDING A PROJECT TODAY WE WILL COVER 3. BUILD & TRAIN MODELS IN SAGEMAKER Amazon Rekognition Amazon S3 AWS Lambda
  7. 7. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 1. MACHINE LEARNING OVERVIEW
  8. 8. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Model training Inference OVERVIEW OF DEEP LEARNING Data
  9. 9. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. DATA Annotate Preprocess Data split
  10. 10. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. MODEL DEVELOPMENT & 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
  11. 11. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 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.
  12. 12. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 2. DEEPLENS OVERVIEW
  13. 13. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 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
  14. 14. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. UNDER THE COVERS- AWS DEEPLENS • Cloud to device • On the device
  15. 15. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. UNDER THE COVERS - CONSOLE
  16. 16. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. UNDER THE COVERS – DEVICE
  17. 17. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 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
  18. 18. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 3. BUILD & TRAIN MODELS IN SAGEMAKER
  19. 19. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. End-to-End Machine Learning Platform Zero Setup Flexible Model Training Pay By The Second AMAZON SAGEMAKER The quickest and easiest way to get ML models from idea to production $
  20. 20. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon SageMaker Fully managed hosting with auto- scaling One-click deployment Pre-built notebooks for common problems Built-in, high performance algorithms Hyperparameter optimization BUILD TRAIN DEPLOY One-click training
  21. 21. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Get Started with Deep Learning in Less than 10 Minutes with AWS DeepLens B u i l d c u s t o m d e e p l e a r n i n g m o d e l s i n t h e c l o u d u s i n g A m a z o n S a g e M a k e r O R u s e t h e c o l l e c t i o n o f p r e - t r a i n e d m o d e l s i n c l u d e d w i t h A W S D e e p L e n s
  22. 22. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. WINNERS OF THE DEEPLENS HACKATHON FIRST PLACE SECOND PLACE THIRD PLACE ReadToMe Created by Alex Schultz ReadToMe is a deep learning enabled application that is able to read books to kids. In this case, reading Green Eggs and Ham, by Dr. Seuss. Dee Created by Matthew Clark Dee is a fun AWS DeepLens interactive device for children. The device asks children to answer questions by showing a picture of the answer. SafeHaven Created by Nathan Stone and Peter McLean SafeHaven uses Alexa and AWS DeepLens to bring peace of mind for vulnerable people and their families. VIEW ALL 23 PROJECTS AT: https://aws.amazon.com/deeplens/community-projects
  23. 23. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 4. Extending a Project: Audience Response Tracking with AWS
  24. 24. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
  25. 25. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Rekognition Image Inference Lambda Amazon S3 Bucket Amazon DynamoDB SageMaker & DeepLens Console Amazon S3 Bucket Recognize Emotions Lambda Training/validation data Cropped Face Images Cropped Face Images Detected Emotions DeepLens Cloud Amazon CloudWatch Detected Emotions
  26. 26. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Now, let’s see it in action….
  27. 27. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Thanks & Wrap-Up Pre-order aws.amazon.com/deeplens/ Learn more aws.amazon.com/deeplens/community-projects Request a workshop Work with your AWS account management team to request a hands-on SageMaker & DeepLens workshop
  28. 28. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Questions?

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