Making sense of Machine Learning for your organization

Transcript

1. © 2019, Amazon Web Services, Inc. or its Affiliates. Making sense of Machine Learning for your organization Antje Barth Technical Evangelist AI and Machine Learning, AWS @anbarth 5 November 2019
2. © 2019, Amazon Web Services, Inc. or its Affiliates. A little about me… Antje Barth, AWS Technical Evangelist AI/ML • Data Enthusiast • AI / ML / Deep Learning • Machine Learning on Kubernetes • Big Data • Ex: MapR, Cisco #CodeLikeAGirl
3. © 2019, Amazon Web Services, Inc. or its Affiliates. Agenda • Machine Learning 101 • AWS AI/ML Offerings • Bringing ML to your organization
4. © 2019, Amazon Web Services, Inc. or its Affiliates. Machine Learning in 10 Minutes
5. © 2019, Amazon Web Services, Inc. or its Affiliates. Classical Programming Machine Learning Data Rules Data Answers Answers Rules What is machine learning?
6. © 2019, Amazon Web Services, Inc. or its Affiliates. A process by which a computer system makes decisions based on rules that it learned on its own What is machine learning?
7. © 2019, Amazon Web Services, Inc. or its Affiliates. Machine Learning in the broader ecosystem: Machine Learning Artificial Intelligence Deep Learning “ability to make decisions” “ability to learn rules” “ability to learn concepts” Broad Niche
8. © 2019, Amazon Web Services, Inc. or its Affiliates. What is machine learning? Step 1: Problem Statement Step 2: Training Step 3: Inference
9. © 2019, Amazon Web Services, Inc. or its Affiliates. How do I get started? Step 1: PROBLEM What am I trying to solve for?
10. © 2019, Amazon Web Services, Inc. or its Affiliates. Supervised vs. Unsupervised vs Reinforcement • Labelled training data • Want to predict labels of new, unlabeled data • Ex: Classification, K-nearest neighbor • Algorithm finds trends in data, optimization is algorithm-reliant • Ex: Automated clustering, k-means, data exploration • Complex problem/reward space • Consecutive actions by agent result in an outcome/score • Ex: Agent for autonomous driving 3 Classes of Learning Problems
11. © 2019, Amazon Web Services, Inc. or its Affiliates. How do I create a model? Step 2: TRAINING
12. © 2019, Amazon Web Services, Inc. or its Affiliates. What is ML: Training Data Training Data: Class 1 Training Data: Class 2
13. © 2019, Amazon Web Services, Inc. or its Affiliates. What is ML: Model Model Decision Boundary
14. © 2019, Amazon Web Services, Inc. or its Affiliates. What is ML: Algorithm The algorithm is not visible in this diagram, because is not an object or property, it is a process. ? Each algorithm behaves differently, and has its own tradeoffs (no objectively best algorithm!)
15. © 2019, Amazon Web Services, Inc. or its Affiliates. How do I use my model? Step 3: INFERENCE
16. © 2019, Amazon Web Services, Inc. or its Affiliates. What is ML: Decision Area Model Decision Boundary Decision Area: Class 1 Decision Area: Class 2
17. © 2019, Amazon Web Services, Inc. or its Affiliates. ML Process in 3 steps: Optimization Parameter Step 1: PROBLEM Step 2: TRAINING Step 3: INFERENCE Determines Gets wrapped as function
18. © 2019, Amazon Web Services, Inc. or its Affiliates. Our mission at AWS Put machine learning in the hands of every developer
19. © 2019, Amazon Web Services, Inc. or its Affiliates. To accomplish this: Built the cloud with the broadest and deepest set of ML capabilities
20. © 2019, Amazon Web Services, Inc. or its Affiliates. MACHINE LEARNING IS HAPPENING IN COMPANIES OF EVERY SIZE AND INDUSTRY Tens of thousands customers have chosen AWS for their ML workloads | More than twice as many customers using ML than any other cloud providers
21. © 2019, Amazon Web Services, Inc. or its Affiliates. Technology Bringing AI into your digital transformation requires a new “stack” that makes it easier to put ML to work
22. © 2019, Amazon Web Services, Inc. or its Affiliates. 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 T R 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 Hosting Amazon SageMaker F P G A S E 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 A 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 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
23. © 2019, Amazon Web Services, Inc. or its Affiliates. 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 T R 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 Hosting Amazon SageMaker F P G A S E 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 A 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 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
24. © 2019, Amazon Web Services, Inc. or its Affiliates. M O D E R N I Z E Y O U R C O N T A C T C E N T E R T O I M P R O V E C U S T O M E R S E R V I C E Voice of the customer analytics | Automated service agents | Multi-lingual text support Workforce forecasting and agent analysis | Next best action recommendation POLLY TRANSCRIBE TRANSLATE COMPREHEND LEX PERSONALIZE PUT AI TO WORK FOR YOUR BUSINESS
25. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Meaningful customer interactions Liberty Mutual uses Amazon Lex and AI Services to develop natural language-driven conversational apps to allow customer service agents to respond to customer requests with real-time and contextual intelligence, improving response time, and quality of service.
26. © 2019, Amazon Web Services, Inc. or its Affiliates. U S E A I S E R V I C E S T O S T R E N G T H E N S A F E T Y A N D S E C U R I T Y REKOGNITION IMAGE COMPREHEND REKOGNITION VIDEO Risk assessment | Threat detection | Identity verification | Alarm prioritization PUT AI TO WORK FOR YOUR BUSINESS
27. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Real-time identity verification Aella Credit uses Amazon Rekognition to analyze images to verify an individual’s identity in real- time without human intervention, allowing it to provide instant loans to eligible customers through its mobile app.
28. © 2019, Amazon Web Services, Inc. or its Affiliates. A U T O M A T E M E D I A W O R K F L O W S T O R E D U C E C O S T S A N D M O N E T I Z E C O N T E N T Media metadata tagging | Highlight clipping | Subtitling and localization | Content moderation | Compliance | Contextual ad insertion REKOGNITION IMAGE REKOGNITION VIDEO COMPREHEND TRANSCRIBE TRANSLATE TEXTRACT SAGEMAKER PUT AI TO WORK FOR YOUR BUSINESS
29. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Enhancing the fan experience Formula 1 uses Amazon SageMaker to create real time insights on how a driver is performing, improving the fan experience on television broadcasts and digital platforms.
30. © 2019, Amazon Web Services, Inc. or its Affiliates. R E D U C E L O C A L I Z A T I O N C O S T S A N D I M P R O V E A C C U R A C Y POLLY TRANSCRIBE TRANSLATE COMPREHEND Website & document translation | Recorded call analysis | Video subtitling PUT AI TO WORK FOR YOUR BUSINESS
31. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Scaling real-time translation Using AWS ML, Lionbridge is able to scale machine translation in order to localize content faster and in more languages. Lionbridge was able to reduce translation costs by 20 percent.
32. © 2019, Amazon Web Services, Inc. or its Affiliates. U N D E R S T A N D T H E V O I C E O F Y O U R C U S T O M E R REKOGNITION IMAGE REKOGNITION VIDEO TRANSLATE TRANSCRIBE COMPREHEND Problem detection | Sentiment analysis | Campaign targeting | Personalized service PUT AI TO WORK FOR YOUR BUSINESS
33. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Analyzing social media for potential food safety issues Chick-fil-A uses Amazon Comprehend to identify key words, phrases, and customer sentiment from social media data to help spot potential food safety related issues.
34. © 2019, Amazon Web Services, Inc. or its Affiliates. P E R S O N A L I Z E C U S T O M E R E X P E R I E N C E S W I T H T A R G E T E D R E C O M M E N D A T I O N S Personalized recommendations | Personalized search | Personalized notifications PERSONALIZE PUT AI TO WORK FOR YOUR BUSINESS
35. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Personalizing customer experiences Domino’s uses Amazon Personalize to customize and scale relevant marketing communications to customers based on time, context, and content, thereby improving and enhancing their experience with the Domino’s brand.
36. © 2019, Amazon Web Services, Inc. or its Affiliates. P R O T E C T U S E R S F R O M U N S A F E C O N T E N T UGC curation | Media compliance marking | Ad adjacency assurance REKOGNITION IMAGE TRANSCRIBE COMPREHEND REKOGNITION VIDEO PUT AI TO WORK FOR YOUR BUSINESS
37. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Moderating photo submissions Coffee Meets Bagel uses AWS ML to identify user- generated photos that need moderation. This reduces the need for human involvement by 97% and decreases the time required for photo approvals from hours to minutes.
38. © 2019, Amazon Web Services, Inc. or its Affiliates. 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 T R 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 Hosting Amazon SageMaker F P G A S E 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 A 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 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
39. © 2019, Amazon Web Services, Inc. or its Affiliates. One-click model training and deployment Train once run anywhere Up to 2x performance increases from model optimization with Neo Up to 70% cost reduction for data labeling using Ground Truth Up to 75% cost reduction for inference with Elastic Inference REDUCE COSTS INCREASE PERFORMANCE EASE-OF-USE AMAZON SAGEMAKER Up to 90% cost reduction with managed spot training Up to 90% scaling efficiency with AWS-optimized TensorFlow SECURITY & COMPLIANCE SOC, PCI, ISO, HIPAA, C5, OSPAR, HITRUST CSF CUSTOM MACHINE LEARNING FOR YOUR BUSINESS
40. © 2019, Amazon Web Services, Inc. or its Affiliates. • Fully-managed training and hosting • Near-linear scaling across 100s of GPU • 75% lower inference costs with Amazon Elastic Inference • 3x faster network throughput with EC2 P3 THE BEST PLACE TO RUN TENSORFLOW Amazon SageMaker is the best place to run TensorFlow in the cloud 65% Stock TensorFlow AWS-optimized TensorFlow 90%
41. © 2019, Amazon Web Services, Inc. or its Affiliates. 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
42. © 2019, Amazon Web Services, Inc. or its Affiliates. 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
43. © 2019, Amazon Web Services, Inc. or its Affiliates. Bringing machine learning to all developers AMAZON SAGEMAKER Collect and prepare training data Amazon SageMaker Ground Truth • Reduce data labeling costs by up to 70% • Work with public and private human labelers • Achieve accurate results quickly Data labeling
44. © 2019, Amazon Web Services, Inc. or its Affiliates. 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
45. © 2019, Amazon Web Services, Inc. or its Affiliates. 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
46. © 2019, Amazon Web Services, Inc. or its Affiliates. 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
47. © 2019, Amazon Web Services, Inc. or its Affiliates. 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
48. © 2019, Amazon Web Services, Inc. or its Affiliates. 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
49. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Fueling product innovation Using AWS ML, Intuit developed ML models that can pull a year’s worth of bank transactions to find deductible business expenses for customers. Using SageMaker, Intuit reduced machine learning deployment time by 90%, from 6 months to 1 week.
50. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. WATCH VIDEO >> Enhancing the fan experience One week of NFL games now creates 3 TB of data. NFL uses AWS ML to analyze telemetry data to predict plays. Computations that could take months to refine now take only weeks or days.
51. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Driving better healthcare outcomes Using AWS ML, GE Healthcare developed an ML model that can learn from thousands of medical scans to detect anomalies more accurately and efficiently, allowing radiologists to prioritize patients needing immediate attention.
52. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Increasing customer engagement Using AWS ML, Tinder analyzes millions of match requests a minute, billions of swipes a day, across more than 190 countries to make the perfect match. Tinder creates tags to highlight photos, resulting in 20% increase in engagement.
53. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Accelerating financial analysis Using AWS ML, Siemens Financial Services developed an NLP model to extract critical information to accelerate investment due diligence, reducing time to summarize diligence documents from 12 hours down to 30 seconds.
54. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Personalizing the gaming experience Using AWS ML, Sony Interactive Entertainment modernized the PlayStation Store, using predictive ML to drive highly personalized customer experiences, improve enterprise data reporting, and drive product feature innovation.
55. © 2019, Amazon Web Services, Inc. or its Affiliates. 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 T R 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 Hosting Amazon SageMaker F P G A S E 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 A 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 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
56. © 2019, Amazon Web Services, Inc. or its Affiliates. 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 T R 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 Hosting Amazon SageMaker F P G A S E 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 A 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 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
57. © 2019, Amazon Web Services, Inc. or its Affiliates. Pulling it all together Setting your organization up for success with AI/ML
58. © 2019, Amazon Web Services, Inc. or its Affiliates. With machine learning, there is no one size fits all solution
59. © 2019, Amazon Web Services, Inc. or its Affiliates. The ideal solution considers the intersection of the following technical specifications: Latency Cost Scalability Customizability
60. © 2019, Amazon Web Services, Inc. or its Affiliates. But it’s important not to forget organizational readiness: Employee Skillset Agility Requirements Foundational Infrastructure
61. © 2019, Amazon Web Services, Inc. or its Affiliates. 1 Create the loop Connect technology initiatives with business outcomes 2 Assess your structured and unstructured data sources Advance your data strategy ? 3 Put machine learning in the hands of your developers Organize for success
62. © 2019, Amazon Web Services, Inc. or its Affiliates. 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
63. © 2019, Amazon Web Services, Inc. or its Affiliates. AWS CLOUD AI/ML DECISION FLOWCHART
64. © 2019, Amazon Web Services, Inc. or its Affiliates. © 2019, Amazon Web Services, Inc. or its Affiliates. Thank you! antje.official antje @anbarth Antje Barth To learn more: AI.aws