An Overview of Machine Learning on AWS

1. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Craig Stires, Head of AI, Analytics, Big Data - Asia Pacific, AWS Olivier Klein, Head of Emerging Tech - Asia Pacific, AWS March 2018 Unlocking New Todays AI and ML on AWS

3. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Machine Learning accessible to many more people A few highly specialized individuals Not long ago Every developer and data scientist Today

4. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. AW S DEEP LEARNING AMI Apache MXNet TensorFlowCaffe2 Torch KerasCNTK PyTorch GluonTheano VISION LANGUAGE Amazon Rekognition Image Amazon Comprehend Amazon Lex Amazon Rekognition Video AWS DeepLensAmazon SageMaker Spark and EMR Amazon Polly Amazon Translate Amazon Transcribe The Amazon machine learning stack PLATFORM SERVICES FRAMEWORKS AND INTERFACES APPLICATION SERVICES

6. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Seamless experience - no more boundaries Seamless experience Remove the hard edges that start and stop an experience Provide customers with an immersive, natural experience that starts and stops without artificial boundaries. These experiences include voice enablement, movement detection, intelligent visual context, and are responsive to intention. Example Use Cases Chatbots and roboadvisors Service fulfilment via Alexa Skills Sentiment detection and response Immersive, enriched multimedia Checkout-free shopping AI-enhanced sales associates Facial detection for personalization Fraud detection and prevention

7. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Autonomous machines - reliability and safety Mechanized labor increases the ability to scale safely Transform operations through autonomous systems -- offloading to machines the undifferentiated or unsafe human tasks and decision making. Systems can perform more efficiently, accurately, and safely at scale. Autonomous Machines Example Use Cases Predictive maintenance Autonomous vehicles Shop floor automation Zone access control and event ID Robotic emergency response Ambient change detection

8. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Scientific breakthrough - golden age of discovery Solve fundamental needs for humans, animals, and the earth Scientific discoveries using deep learning require tremendous compute capabilities to build and validate models -- now available. Frameworks and development platforms allow for a broadened community of users from scientists to analysts. Scientific Breakthrough Example Use Cases Patient treatment & safety Agricultural yield optimization Urban maintenance Livestock health and production Quantum / particle advancements Utility grid efficiency

11. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. AW S DEEP LEARNING AMI Apache MXNet TensorFlowCaffe2 Torch KerasCNTK PyTorch GluonTheano VISION LANGUAGE Amazon Rekognition Image Amazon Comprehend Amazon Lex Amazon Rekognition Video AWS DeepLensAmazon SageMaker Spark and EMR Amazon Polly Amazon Translate Amazon Transcribe The Amazon machine learning stack

12. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Ingest ServingData sources Modern data architecture Insights to enhance business applications, new digital services Transactions Web logs / cookies ERP Data analysts Data scientists Business users Engagement platformsConnected devices Automation / events DATA PIPELINES EVENT PIPELINES Data Event Insights Data Lake Social media

13. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Ingest ServingData sources Modern data architecture Insights to enhance business applications, new digital services Transactions Web logs / cookies ERP Data analysts Data scientists Business users Engagement platformsConnected devices Automation / events DATA PIPELINES EVENT PIPELINES Data Event Insights Data Lake ML / Analytics Social media

14. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Ingest ServingData sources Modern data architecture Insights to enhance business applications, new digital services Transactions Web logs / cookies ERP Data analysts Data scientists Business users Engagement platformsConnected devices Automation / events DATA PIPELINES EVENT PIPELINES Data Event Action Insights Data Lake ML / Analytics Predict / Recommend AI Services Social media

15. Building with Artificial Intelligence

16. Hardware & Learning algorithms Fit a function to the data Fit a network structure to the data

17. Statistical Machine Learning Deep Learning Machine Learning Feature engineeringData Data Automatically identifies features Model Model Unseen Sample Prediction Unseen Sample Prediction

18. Artificially Intelligent + + Unique Individuality Interact Naturally

19. Natural Language Understanding Computer VisionVoice and ASR Forecasting Recommendations Interact Naturally Unique Individuality Clustering

20. Alexa, Hello!

21. Extend capabilities with the help of an open ecosystem! Amazon Echo Alexa Skill AWS Lambda External API Service

22. AW S DEEP LEARNING AMI Apache MXNet TensorFlowCaffe2 Torch KerasCNTK PyTorch GluonTheano VISION LANGUAGE Amazon Rekognition Image Amazon Comprehend Amazon Lex Amazon Rekognition Video AWS DeepLensAmazon SageMaker Spark and EMR Amazon Polly Amazon Translate Amazon Transcribe The Amazon machine learning stack

23. Amazon Transcribe: Automatic Speech Recognition Time stamps and confidence scores Support for both regular and telephony audio Punctuation § Detect multiple speakers Custom vocabulary

24. Amazon Comprehend: NLP 😃 Sentiment Entities Languages Key phrases Topic modeling POWERED BY DEEP LEARNING

25. Amazon.com, Inc. is located in Seattle, WA and was founded July 5th, 1994 by Jeff Bezos. Our customers love buying everything from books to blenders at great prices Named Entities • Amazon.com: Organization • Seattle, WA : Location • July 5th,1994: Date • Jeff Bezos : Person Keyphrases • Our customers • books • blenders • great prices Sentiment • Positive Language • English Text Analysis

26. Call center insights Transcribe 8Khz call recordings with high accuracy Analyze the text with Amazon Comprehend Visualize results on Amazon QuickSight Amazon Transcribe Amazon Comprehend Amazon Connect Amazon Quicksight

27. Amazon Lex Conversational interfaces for your applications, powered by the same Natural Language Understanding (NLU) & Automatic Speech Recognition (ASR) models as Alexa Voice and text “chatbots” Integrates with call centers Voice interactions on mobile, web, and devices Text interaction with Slack, Twilio SMS, Kik, Facebook Messenger Enterprise connectors

28. Intents A particular goal that the user wants to achieve Utterances Spoken or typed phrases that invoke your intent Slots Data the user must provide to fulfill the intent Prompts Questions that ask the user to input data Fulfillment The business logic required to fulfill the user’s intent BookHotel

29. Amazon Rekognition Object and Scene Detection Facial Analysis Face Recognition Text in Image Deep learning-based computer vision service for images and video Unsafe Image Detection Celebrity Recognition

30. Amazon Rekognition Videos Pictures Objects Scenes Sentiments Emotions Celebrities Faces

31. Station DepartureArrival

32. Station DepartureArrival

33. Arrival Station Departure

34. Computer Vision Implementation to identify empty space and detect object misplacements

35. A fully managed service that enables data scientists and developers to quickly and easily build machine-learning based models into production smart applications. Amazon SageMaker End-to-End Machine Learning Platform In-Built ML Algorithms Flexible Model Training Pay by the second

36. Amazon SageMaker BUILD DEPLOY TRAIN

37. Deploy model in production Train and tune models Setup & Manage environment for training Choose & optimise your ML model Scale and manage the production environment Amazon SageMaker Pre-built notebooks for common problems BUILD

38. Amazon SageMaker One-click Training TRAIN Deploy model in production Train and tune models Scale and manage the production environment Built-in, High performance Algorithms Pre-built notebooks for common problems BUILD

39. SageMaker In-Built Algorithms K-means Clustering PCA Neural Topic Modelling Factorisation Machines Linear Learner – Regression XGBoost Latent Dirichlet Allocation Image Classification Seq2Seq Linear Learner Binary Classification DeepAR Forecasting

40. K-Means Clustering

41. Matrix Factorization

42. Retrain classification Feature Extraction Image Classification Transfer Learning Convolutional Neural Network

43. MXNet & TensorFlow SDK TensorFlow SDK MXNet (Gluon) SDK SageMaker Built-in Algorithms K-means Clustering PCA Neural Topic Modelling Factorisation Machines Linear Learner – Regression XGBoost Latent Dirichlet Allocation Image Classification Seq2Seq Linear Learner – Classification DeepAR Forecasting Bring Your Own Algorithms ML Algorithms R MXNet TensorFlow Caffe PyTorch Keras CNTK … Apache Spark Estimator Apache Spark Python library Apache Spark Scala library Training Using Amazon SageMaker Amazon EMR

44. Amazon SageMaker TRAIN Deploy model in production Scale and manage the production environment Pre-built notebooks for common problems BUILD Built-in, High performance Algorithms One-click Training Hyperparameter Optimisation

45. Amazon SageMaker One-click Deployment Scale and manage the production environment DEPLOY Pre-built notebooks for common problems Built-in, High performance Algorithms One-click Training Hyperparameter Optimisation BUILD TRAIN

46. Train model in the cloud Run model at the edge AWS Greengrass AWS IoT Tesla V100 120 TFLOPS Amazon EC2

47. Amazon SageMaker Fully managed hosting with Auto-scaling DEPLOY One-click Deployment One-click Deployment Pre-built notebooks for common problems Built-in, High performance Algorithms One-click Training Hyperparameter Optimisation BUILD TRAIN

48. Amazon Sagemaker AWS Lambda Greengrass Core Alexa Skill Shadow Edge Amazon Echo object-detection

49. Join us to learn how Amazon and pioneering businesses build a culture which drives innovation at scale. Register Today! #AWSOnAir @AWSCloudANZ #AWSSummit

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