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Artifical Intelligence and Machine Learning 201, AWS Federal Pop-Up Loft

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Come join us for a one-day session where you will learn about the science of computer vision (CV) and train custom CV models utilizing Amazon SageMaker. In this course, you'll learn about Amazon's managed machine learning platform and utilize publicly available real-world ground truth data sets to train models leveraging the built-in ML algorithms of Amazon SageMaker to detect objects and buildings. This is a hands-on workshop, attendees should bring your own laptops.

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Artifical Intelligence and Machine Learning 201, AWS Federal Pop-Up Loft

  1. 1. 1© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 1© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Building Models for Satellite Imagery Using Amazon SageMaker and xView/SpaceNet Dataset Mike Liu Solutions Architect – AI/ML liumike@amazon.com AWS | Federal Pop-Up Loft AI/ML 201
  2. 2. 2© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | • 9-9:15 - Welcome & Introductions • 9:15-10:15 - Introduction to Amazon ML Stack & SageMaker • 10:15-10:30 - Break • 10:30-11 - Lab 1: Create Your First SageMaker Notebook • 11-12PM - Computer Vision 101 • 12PM-1 - Lunch • 1-2 - Lab 2: xView Object Detection using Amazon SageMaker • 2-3 - Lab 3: Training SpaceNet Building’s Dataset • 3-3:15 - Workshop Cost Analysis • 3:15-3:30 - Wrap up and Review AGENDA
  3. 3. 3© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 3© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Welcome & Introductions
  4. 4. 4© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 4© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Introduction to Amazon ML Stack & SageMaker
  5. 5. 5© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | FRAMEWORKS INTERFACES INFRASTRUCTURE AI Services Broadest and deepest set of capabilities THE AWS ML STACK VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS ML Services ML Frameworks + Infrastructure 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 X F O R E C A S TR E K O G N I T I O N I M A G E R E K O G N I T I O N V I D E O T E X T R A C T P E R S O N A L I Z E Ground Truth Notebooks Algorithms + Marketplace Reinforcement Learning Training Optimization Deployment HostingAmazon SageMaker F P G A SE C 2 P 3 & P 3 D N E C 2 G 4 E C 2 C 5 I N F E R E N T I AG 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 D L C O N T A I N E R S & A M I s E L A S T I C K U B E R N E T E S S E R V I C E E L A S T I C C O N T A I N E R S E R V I C E
  6. 6. 6© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | FRAMEWORKS INTERFACES INFRASTRUCTURE AI Services Broadest and deepest set of capabilities THE AWS ML STACK VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS ML Services ML Frameworks + Infrastructure 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 X F O R E C A S TR E K O G N I T I O N I M A G E R E K O G N I T I O N V I D E O T E X T R A C T P E R S O N A L I Z E Ground Truth Notebooks Algorithms + Marketplace Reinforcement Learning Training Optimization Deployment HostingAmazon SageMaker F P G A SE C 2 P 3 & P 3 D N E C 2 G 4 E C 2 C 5 I N F E R E N T I AG 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 D L C O N T A I N E R S & A M I s E L A S T I C K U B E R N E T E S S E R V I C E E L A S T I C C O N T A I N E R S E R V I C E
  7. 7. 7© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers 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
  8. 8. 8© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers 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 Pre-built notebooks for common problems
  9. 9. 9© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | TRAINING DATA Successful models require high-quality data
  10. 10. 10© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | TRAINING DATA
  11. 11. 11© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Build highly accurate training datasets and reduce data labeling costs by up to 70% using machine learning AMAZON SAGEMAKER GROUND TRUTH
  12. 12. 12© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | AMAZON SAGEMAKER GROUND TRUTH
  13. 13. 13© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers AMAZON SAGEMAKER Collect and prepare training data Choose and optimize your ML algorithm Pre-built notebooks for common problems Built-in, high performance algorithms • K-Means Clustering • Principal Component Analysis • Neural Topic Modelling • Factorization Machines • Linear Learner (Regression) • BlazingText • Reinforcement learning • XGBoost • Topic Modeling (LDA) • Image Classification • Seq2Seq • Linear Learner (Classification) • DeepAR Forecasting
  14. 14. 14© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ML algorithms and models available instantly AWS MARKETPLACE FOR MACHINE LEARNING Subscribe in a single click Available in Amazon SageMaker KEY FEATURES Automatic labeling via machine learning IP protection Automated billing and metering Browse or search AWS Marketplace S E L L E R S Broad selection of paid, free, and open-source algorithms and models Data protection Discoverable on your AWS bill B U Y E R S
  15. 15. 15© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers 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 Pre-built notebooks for common problems Built-in, high performance algorithms One-click training
  16. 16. 16© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers 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 Pre-built notebooks for common problems Built-in, high performance algorithms One-click training Optimization
  17. 17. 17© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | Bringing machine learning to all developers 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 Pre-built notebooks for common problems Built-in, high performance algorithms One-click training Optimization One-click deployment
  18. 18. 18© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 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 Pre-built notebooks for common problems Built-in, high performance algorithms One-click training Optimization One-click deployment Fully managed with auto-scaling, health checks, automatic handling of node failures, and security checks Bringing machine learning to all developers AMAZON SAGEMAKER
  19. 19. 19© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | One-click model training and deployment Train once run anywhere 10x better algorithm performance 2x performance increases from model optimization with Neo 70% cost reduction for data labeling using Ground Truth 75% cost reduction for inference with Elastic Inference REDUCE COSTS INCREASE PERFORMANCE EASE-OF-USE C U S T O M M A C H I N E L E A R N I N G F O R Y O U R B U S I N E S S AMAZON SAGEMAKER
  20. 20. 20© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | FRAMEWORKS INTERFACES INFRASTRUCTURE AI Services Broadest and deepest set of capabilities THE AWS ML STACK VISION SPEECH LANGUAGE CHATBOTS FORECASTING RECOMMENDATIONS ML Services ML Frameworks + Infrastructure 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 X F O R E C A S TR E K O G N I T I O N I M A G E R E K O G N I T I O N V I D E O T E X T R A C T P E R S O N A L I Z E Ground Truth Notebooks Algorithms + Marketplace Reinforcement Learning Training Optimization Deployment HostingAmazon SageMaker F P G A SE C 2 P 3 & P 3 D N E C 2 G 4 E C 2 C 5 I N F E R E N T I AG 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 D L C O N T A I N E R S & A M I s E L A S T I C K U B E R N E T E S S E R V I C E E L A S T I C C O N T A I N E R S E R V I C E
  21. 21. 21© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | HOW WE CAN HELP • Brainstorming • Custom modeling • Training • Work side-by-side with Amazon experts ML Solutions Lab • Practical education on ML for new and experienced practitioners • Based on the same material used to train Amazon developers Machine Learning Training and Certification
  22. 22. 22© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 22© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | QUESTIONS?
  23. 23. 23© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 23© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | https://tinyurl.com/aiml201 Lab 1: Create Your First SageMaker Notebook
  24. 24. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark CV-101 | Computer Vision Intro
  25. 25. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark The Machine Learning Journey https://www.geospatialworld.net/blogs/difference-between-ai%EF%BB%BF-machine-learning-and-deep-learning/
  26. 26. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Supervised Learning • The algorithm is given a set of training examples where the data and target are known. It can then predict the target value for new datasets, containing the same attributes • Human intervention and validation required Example: Photo classification and tagging Buliding Car Person OR OR
  27. 27. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Supervised Learning : How Machines Learn Input Label Machine Learning AlgorithmBuilding Prediction Car Training Data ? Label Building Adjust Model
  28. 28. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark How do we apply this to aerial images?
  29. 29. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
  30. 30. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Most Pre-Trained Models Don’t Work
  31. 31. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Successful models require high-quality training data
  32. 32. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark General Categories of Computer Vision Algorithms 1. Image Classification • Convolutional Neural Network (CNN) 2. Object Detection • Region-Based Convolution Neural Network (R-CNN) 3. Semantic Segmentation • Fully Convolutional Network (FCN) DogDog
  33. 33. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Convolutions! (Who took Electrical Engineering courses in college?)
  34. 34. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Let’s Walkthrough an Example…. Image Credit: https://towardsdatascience.com/a-comprehensive-guide-to-convolutional-neural-networks-the-eli5-way-3bd2b1164a53
  35. 35. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Region-Based Convolutional Neural Network Image Credit: https://towardsdatascience.com/r-cnn-fast-r-cnn-faster-r-cnn-yolo-object-detection-algorithms-36d53571365e
  36. 36. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Fully Convolutional Network
  37. 37. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark What Are Some More Sophisticated Architectures? • Image Classification • ResNet • Inception V4 • NASNet • Object Detection • Single Shot Multibox Detector (SSD) • YOLOv3 • Feature Pyramid Networks (FPN) with Faster R-CNN • Semantic Segmentation • U-Net • Mask R-CNN • DeepLabv3+
  38. 38. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Supervised Learning : How Machines Learn Input Label Machine Learning AlgorithmBuilding Prediction Car Training Data ? Label Building Adjust Model
  39. 39. 39© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 39© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | https://tinyurl.com/aiml201 Lab 2: xView Object Detection using Amazon SageMaker
  40. 40. 40© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 40© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | https://tinyurl.com/aiml201 Lab 3: Training the SpaceNet Building’s Dataset
  41. 41. 41© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | 41© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | ML Cost Example Analysis
  42. 42. 42© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | WORKSHOP COST ANALYSIS (ASSUMPTIONS) SageMaker Notebook Instance ml.m5.xlarge Cost $ 0.269 Storage 5GB Runtime 6hr Data Transfer 5GB SageMaker Model Training Instance ml.p3.8xlarge Cost 17.136 Storage 50GB Runtime 0.35hr Data Transfer 5GB SageMaker Endpoint Instance ml.m5.xlarge Cost $ 0.269 Storage 5GB Runtime 6hr Data Transfer 5GB
  43. 43. 43© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | WORKSHOP COST ANALYSIS Service Description Region Cost/Event Event Qty Total SageMaker Notebook Instance US East $ 0.269 Per Hour 6.00 $ 1.61 SageMaker Notebook Storage US East $ 0.140 GB-month 0.04 $ 0.01 SageMaker Notebook Data Transfer US East $ 0.016 GB 5.00 $ 0.08 SageMaker Model Training US East $ 17.136 Per Hour 0.35 $ 6.00 SageMaker Model Training Storage US East $ 0.140 GB-month 0.02 $ 0.00 SageMaker Endpoint US East $ 0.269 Per Hour 6.00 $ 1.61 SageMaker Endpoint Storage US East $ 0.140 GB-month 0.04 $ 0.01 SageMaker Endpoint Data Transfer US East $ 0.016 GB 5.00 $ 0.08 Total $ 9.40
  44. 44. 44© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | WORKSHOP COST ANALYSIS (ASSUMPTIONS) SageMaker Notebook Instance ml.m5.xlarge Cost $ 0.269 Storage 5GB Runtime 480hr Data Transfer 5GB SageMaker Model Training Instance ml.p3.8xlarge Cost 17.136 Storage 50GB Runtime 0.35hr Data Transfer 5GB SageMaker Endpoint Instance ml.m5.xlarge Cost $ 0.269 Storage 5GB Runtime 960hr Data Transfer 5GB
  45. 45. 45© 2019 Amazon Web Services, Inc. or its affiliates. All rights reserved | WORKSHOP COST ANALYSIS (NO TERMINATION) Service Description Region Cost/Event Event Qty Total SageMaker Notebook Instance US East $ 0.269 Per Hour 480.00 $ 129.12 SageMaker Notebook Storage US East $ 0.140 GB-month 3.23 $ 0.45 SageMaker Notebook Data Transfer US East $ 0.016 GB 5.00 $ 0.08 SageMaker Model Training US East $ 17.136 Per Hour 0.35 $ 6.00 SageMaker Model Training Storage US East $ 0.140 GB-month 0.02 $ 0.00 SageMaker Endpoint US East $ 0.269 Per Hour 960.00 $ 258.24 SageMaker Endpoint Storage US East $ 0.140 GB-month 6.45 $ 0.90 SageMaker Endpoint Data Transfer US East $ 0.016 GB 5.00 $ 0.08 Total $ 394.87

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