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Drive Digital Transformation Using Machine Learning

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Learn to identify use cases for machine learning (ML), acquire best practices to frame problems in a way that key stakeholders and senior management can understand and support, and help create the right conditions for delivering successful ML-based solutions to your business.

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Drive Digital Transformation Using Machine Learning

  1. 1. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C TO R S U M M I T Drive digital transformation using machine learning Neil Mackin Technical Business Development AWS
  2. 2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark of digital transformation initiatives supported by AI in 201940% - IDC 2018 © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  3. 3. Drive digital transformation using machine learning •“Art of the possible” + “Art of the practical” Target Application Key Ingredients: • Business Value: the results must be measurable against specific business objectives and metrics • Ability to Execute: the chosen target must be realistically feasible • Data Availability: the information sources must be available & accessible
  4. 4. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Our mission at AWS Put machine learning in the hands of every developer © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  5. 5. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. • CONVERTING THE POWER OF MACHINE LEARNING INTO BUSINESS VALUE • MAKING THE BEST USE OF A DATA SCIENTISTS’ TIME • EMBEDDING MACHINE LEARNING INTO THE FABRIC OF YOUR BUSINESS While the power of ML is unrivaled, “data scientists spend around 80% of their time on preparing and managing data for analysis” … hence only 20% of their time is used to derive insights The value of data science relies upon operationalizing models within business applications and processes, yet “50% of the predictive models [built] don’t get implemented” While “60% of companies agree that big data will help improve their decision making and competitiveness … only 28% indicate that they are currently generating strategic value from their data” What is AWS AI/ML solving for? 1 2 3
  6. 6. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Our unique approach Customer-focused 90%+ of our ML roadmap is defined by customers Breadth & depth More AI and ML services in production than any other provider Embedded R&D Customer-centric approach to advancing the state of the art Security & analytics Deepest set of security and encryption features, with robust analytics capabilities Multi-framework Support for the most popular frameworks Pace of innovation 200+ new ML launches in the last year © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  7. 7. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark customers have used machine learning on AWS 10,000+ AWS holds the top spots on Stanford’s deep learning benchmark, DAWN, for fastest training time, lowest cost, lowest inference latency ofTensorFlow projects in the cloud run on AWS85% of deep learning in the cloud runs on AWS 81% © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  8. 8. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Nonprofit/HealthcareGovernmentEducation InstitutionsEdTechs Federal/CivilState/Local Shotspotter Washington County Sheriff’s Office
  9. 9. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark CultureTechnology © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  10. 10. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Bringing AI into your digital transformation requires a new “stack” that makes it easier to put ML to work Technology © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  11. 11. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark M L F R A M E W O R K S & I N F R A S T R U C T U R E A I S E R V I C E S Vision | Documents | Speech | Language | Chatbots | Forecasting | Recommendations M L S E R V I C E S Data labeling | Pre-built algorithms & notebooks | One-click training and deployment Build, train, and deploy machine learning models fast Easily add intelligence to applications without machine learning skills Flexibility & choice, highest-performing infrastructure Support for ML frameworks | Compute options purpose-built for ML © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  12. 12. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark M L F R A M E W O R K S & I N F R A S T R U C T U R E The Amazon ML Stack: Broadest & Deepest Set of Capabilities A I S E R V I C E S R E K O G N I T I O N I M A G E 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 XR E K O G N I T I O N V I D E O Vision Speech Chatbots A M A Z O N S A G E M A K E R B U I L D T R A I N F O R E C A S TT E X T R A C T P E R S O N A L I Z E D E P L O Y Pre-built algorithms & notebooks Data labeling (G R O U N D T R U T H ) One-click model training & tuning Optimization ( N E O ) One-click deployment & hosting M L S E R V I C E S F r a m e w o r k s I n t e r f a c e s I n f r a s t r u c t u r e E C 2 P 3 & P 3 d n E C 2 C 5 F P G A s G 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 Models without training data (REINFORCEMENT LEARNING) Algorithms & models ( A W S M A R K E T P L A C E ) Language Forecasting Recommendations NEW NEWNEW NEW NEW NEWNEW NEW NEW RL Coach © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  13. 13. Amazon Rekognition Object, Scene & Activity Recognition Facial Recognition Facial Analysis Tracking Unsafe Content Detection Celebrity Recognition Text in Images D e e p l e a r n i n g - b a s e d i m a g e a n d v i d e o a n a l y s i s
  14. 14. Fighting Human Trafficking & Rescuing Victims • Uses Amazon Rekognition to power their Traffic Jam FaceSearch tool • “Without Traffic Jam, investigators are left to manually sift through thousands of online ads. This means they sit at their computer, with a picture of the victim taped to their screen, and compare every photo they see online in the hope that they might find a match. Using AI technology, like Amazon Rekognition, this critical task can now be done with more accuracy and within seconds as compared to days, which is so important in cases where detectives have limited time to find the victim before he or she is moved to the next city.” • - Emily Kennedy, President & Co-Founder, Marinus Analytics
  15. 15. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Given this photo of Andy Jassy Tell me if you find him in this image… Amazon Rekognition: Confidence level that source face is in target photo: 98 % Amazon Rekognition Images © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  16. 16. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Rekognition Images bucket = 'my-photos-bucket' key_s = 'andy_jassy_headshot.png' key_t = 'interview.png' rek_client=boto3.client('rekognition', 'ap-southeast-2') response = rek_client.compare_faces( SimilarityThreshold = 75, SourceImage={ 'S3Object': { 'Bucket': bucket, 'Name': key_s, } }, TargetImage={ 'S3Object': { 'Bucket': bucket, 'Name': key_t, } },) confidence = response['FaceMatches'][0]['Similarity'] print('Confidence level that source face is in target photo: ',confidence,'%') © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  17. 17. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon Rekognition Images bucket = 'my-photos-bucket' key_s = 'andy_jassy_headshot.png' key_t = 'interview.png' rek_client=boto3.client('rekognition', 'ap-southeast-2') response = rek_client.compare_faces( SimilarityThreshold = 75, SourceImage={ 'S3Object': { 'Bucket': bucket, 'Name': key_s, } }, TargetImage={ 'S3Object': { 'Bucket': bucket, 'Name': key_t, } },) confidence = response['FaceMatches'][0]['Similarity'] print('Confidence level that source face is in target photo: ',confidence,'%')
  18. 18. Powerful speech & 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
  19. 19. Automated workflow for efficient captioning of videos • Echo360 provides leading video platform technology that helps instructors and students record, stream, manage and share interactive video • The platform captures professor lectures at 650 institutions, in 30 countries, 8,000 classrooms for over 3M students. • Amazon Transcribe provides high-quality transcripts for each video, enabling more powerful search, lower captioning cost, and enhanced note-taking, making learning assets more valuable and accessible to students.
  20. 20. Amazon Comprehend D i s c o v e r i n s i g h t s a n d r e l a t i o n s h i p s i n t e x t Entities Key Phrases Language Sentiment Amazon Comprehend
  21. 21. Amazon Comprehend STORM WORLD SERIES STOCK MARKET WASHINGTON LIBRARY OF NEWS ARTICLES Amazon Comprehend D i s c o v e r i n s i g h t s a n d r e l a t i o n s h i p s i n t e x t
  22. 22. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark M L F R A M E W O R K S & I N F R A S T R U C T U R E The Amazon ML Stack: Broadest & Deepest Set of Capabilities A I S E R V I C E S R E K O G N I T I O N I M A G E 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 XR E K O G N I T I O N V I D E O Vision Speech Chatbots A M A Z O N S A G E M A K E R B U I L D T R A I N F O R E C A S TT E X T R A C T P E R S O N A L I Z E D E P L O Y Pre-built algorithms & notebooks Data labeling (G R O U N D T R U T H ) One-click model training & tuning Optimization ( N E O ) One-click deployment & hosting M L S E R V I C E S F r a m e w o r k s I n t e r f a c e s I n f r a s t r u c t u r e E C 2 P 3 & P 3 d n E C 2 C 5 F P G A s G 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 Models without training data (REINFORCEMENT LEARNING) Algorithms & models ( A W S M A R K E T P L A C E ) Language Forecasting Recommendations NEW NEWNEW NEW NEW NEWNEW NEW NEW RL Coach © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  23. 23. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark 1 2 3 © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  24. 24. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Amazon SageMaker Fast & accurate data labeling Built-in, high performance algorithms & notebooks BUI LD 1 One-click training and tuning T R AI N Model optimization 2 Fully managed hosting with auto-scaling and elastic inference One-click deployment DE PLOY 3 © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  25. 25. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark 90+ New Enhancements to SageMaker this Year MXNet 1.3 container | CloudTrail integration for audit logs |TensorFlow 1.7 Containers | Automatic ModelTuning—Add/Delete tags | Jupyter Notebooks IP Filtering Region expansion to SFO | Image Classification Multi-label Support |TensorFlow and MXNet Containers—Open Sourcing and Local Mode | PyTorch pre-built container Region expansion to PDT | Batch customer VPC | PCI DSS Compliance | XGBoost Instance Weights | NTM—vocab, metrics, and subsampling Anomaly Detection (Random Cut Forest) Algorithm | Deep AR algorithm | SageMaker region expansion to ICN | | Hyperparameter tuning job cloning on the console Region expansion to BOM | GDPR compliance | BlazingText Enhancements | TensorFlow 1.9 Container | Intel RL Coach | Notebook bootstrap script Autoscaling console | PyTorch 1.0 container | Customer VPC support for training and hosting | PrivateLink support for SageMaker inferencing APIs Horovod support inTensorFlow Container |Variable sizes for notebook EBS volumes |nbexample support in SageMaker notebook instances |Tag-based access control Automatic Model Tuning—early stopping | IP Insights algorithm | Chainer 4.1 Container | Region expansion to SIN Built-in Algorithms Pipe Mode Support TensorFlow 1.8Container |Region expansion toFRA |Training job cloning in console |Algorithm Pipe mode enhancements |Pipe mode support for text, recordIO, and images TensorFlow 1.5, MXNet 1.0, and CUDA 9 Support | DeepAR Algorithm Enhancements | Linear Learner Multi-class Classification | TensorFlow 1.10 Container Region expansion toYUL | BlazingText Algorithm | Batch KMS | k-nearest neighbors | Object detection |Chainer pre-built container | Apache Airflow integration Amazon SageMaker Hosting custom header attribute | Metrics Support inTraining Jobs |Object2vec |TensorFlow container enhancements |CloudFormation support PrivateLink support for SageMaker Control Plane | MXNet 1.2 Container | HIPAA compliance | Ground Truth | Python SDK Marketplace support Git integration for SageMaker notebooks | Pipe mode support for TensorFlow | ml.p3.2xlarge notebook instances | Internet-free notebook instances Semantic segmentation algorithm | SageMaker Reinforcement Learning support | Linear Learner Improvements | SageMaker Batch Transform Region expansion to NRT | High Performance I/O streaming in PIPE Mode | Pause/resume for active learning algorithms | Pre-built scikit-learn container Step Functions for SageMaker | KMS support for training and hosting | Incremental learning algorithm enhancements |TensorFlow 1.11 container | NTM feature release Deep Learning Compiler | ONNX Support for Frameworks and Algorithms |Full instance type support | Pipe mode CSV support | Region expansion to LHR Incremental training platform support | Login anomaly detection algorithm | Serial inference pipeline | Experiment Management | Region expansion to SYD MXNet container enhancements | Automatic Model Tuning | Automatic Model Tuning—incremental tuning | Spark MLeap 1P container TensorFlow 1.6 and MXNet 1.1 Containers | Region expansion to SIN | Mead Notebook PrivateLink Support | Linear Learner sparsity support © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  26. 26. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark 1 2 3 Amazon SageMaker: Build, Train, and Deploy ML Models at Scale © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  27. 27. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Amazon SageMaker: Build, Train, and Deploy ML Models at Scale © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  28. 28. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Amazon SageMaker: Build, Train, and Deploy ML Models at Scale RL Coach © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  29. 29. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Amazon SageMaker: Build, Train, and Deploy ML Models at Scale © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  30. 30. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Amazon SageMaker: Build, Train, and Deploy ML Models at Scale G R E E N G R A S SE C 2 C 5 © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  31. 31. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Amazon SageMaker: Build, Train, and Deploy ML Models at Scale © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  32. 32. Saving lives with Amazon SageMaker Harnessing data and analytics across hardware, software, and biotech, GE Healthcare is transforming healthcare by delivering better outcomes for providers and patients. • Amazon SageMaker allows GE Healthcare to access powerful artificial intelligence tools and services to advance improved patient care. “The scalability of Amazon SageMaker, and its ability to integrate with native AWS services, adds enormous value for us. We are excited about how our continued collaboration between the GE Health Cloud and Amazon SageMaker will drive better outcomes for our healthcare provider partners and deliver improved patient care.” - Sharath Pasupunuti, AI Engineering Leader
  33. 33. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C TO R S U M M I T •RADIX. AI
  34. 34. RADIX.AI I ● Job matching is core to ● Job matching with deep learning ● Result: improved matching Outline 34
  35. 35. RADIX.AI I VDAB helps Flemish citizens develop their careers 35
  36. 36. RADIX.AI I Matching is at the heart of VDAB Jobsuggesties Jouw jobsuggesties Jouw jobsuggesties 36
  37. 37. RADIX.AI I Can AI improve matching? 37 Brussel Babysitter EN License B Elsene Nanny … speaks English … … drives the kids to school …
  38. 38. RADIX.AI I Can AI do more? 38 Manual work No look-alikes Dutch only nl
  39. 39. RADIX.AI I Radix.ai is a team of engineers that build AI services
  40. 40. RADIX.AI I Artificial Intelligence DL AI ML 40 Is the automation of tasks that require intelligence
  41. 41. RADIX.AI I Machine Learning AI ML 41 ES DL Is a technology to achieve AI with algorithms that learn from data ML AI
  42. 42. RADIX.AI I Deep Learning AI ML 42 ES DL Is a particular type of Machine Learning model ML AI
  43. 43. RADIX.AI I Why Deep Learning? ① Scale improves performance 43 Traditional ML models E.g., SVM, GP, RF, LR Small NN Medium NN Large NN Amount of data ModelPerformance [1] Adapted from Andrew Ng, Extract Data Conference, 2015 (1M params) (10M params) (100M params)
  44. 44. RADIX.AI I Nanny Babysitter
  45. 45. RADIX.AI I 45 h1 h2 h3 king – man + woman = Why Deep Learning? ② Reads natural language
  46. 46. RADIX.AI I The model learns from historical matches 46 .9 Matching score Profiles, Jobs, and Interest Mutual interest estimation 46 Deep Learning
  47. 47. RADIX.AI I Improved matching. Try it out at vdab.be! 47 Brussel Babysitter EN License B Elsene Nanny … speaks English … … drives the kids to school …
  48. 48. RADIX.AI I Extra features 48 AI Self-learning Four-way matching en nl fr de Multi-lingual en nl fr de
  49. 49. RADIX.AI I Example 1 49 Woodworking Child care Playground builder
  50. 50. RADIX.AI I Example 2 50 Social work Educator Crisis relief worker
  51. 51. RADIX.AI I Example 3 51 Operational coordinator Lean coach
  52. 52. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C TO R S U M M I T
  53. 53. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark CultureTechnology © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
  54. 54. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T ML has whole system impact Disruption to established ways of working Laser focus upon Business Value Organizational competency – not just technical Need for Leadership Art of the Practical Leading with ML
  55. 55. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T Keys to Success Ethics , Data Compliance and Information Security Invest in scoping business problems Avoid poor implementations that amplify bad decisions
  56. 56. © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T Breadth of skills Protection against unconscious bias Drive collaboration between technical and business functions Keys to Success Diversity in your team https://commons.wikimedia.org/wiki/File:Survivorship-bias.png
  57. 57. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Assess your structured and unstructured data sources Create the loop 1. Connect technology initiatives with business outcomes Advance your data strategy Put machine learning in the hands of your developers Organize for success 2. 3. ?
  58. 58. Thank you! © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.P U B L I C S E C TO R S U M M I T Neil Mackin nemackin@amazon.com

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