Innovation Track AWS Cloud Experience Argentina - Democratizing Artificial Intelligence with AWS
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Amazon SageMaker is a fully managed machine learning platform that allows developers and data scientists to quickly build, train, and deploy machine learning models at scale. It provides a number of tools including pre-built algorithms, notebooks for common problems, one-click training and deployment, and automatic scaling of production models. More than 10,000 customers are using Amazon SageMaker.
Innovation Track AWS Cloud Experience Argentina - Democratizing Artificial Intelligence with AWS
- 1. 2 0 1 9 #AWSCLOUDEXPERIENCE
- 2. Democratizing Artificial Intelligence with AWS María Gaska AI/ML Solution Architect Amazon Web Services
- 3. Machine Learning at Amazon: A long heritage Voice driven interactions Fulfillment automation & inventory management Personalized recommendations Drones Inventing entirely new customer experiences
- 4. Our mission at AWS Put machine learning in the hands of every developer
- 5. More machine learning happens on AWS
- 6. The Amazon Machine Learning stack A I S E R V I C E S (App developers with little knowledge of ML) A m a z o n R e k o g n i t i o n I m a g e A m a z o n P o l l y A m a z o n T r a n s c r i b e A m a z o n T r a n s l a t e A m a z o n C o m p r e h e n dA m a z o n L e x A m a z o n R e k o g n i t i o n V i d e o Vision Speech LanguageChatbots A m a z o n F o r e c a s t Forecasting A m a z o n T e x t r a c t A m a z o n P e r s o n a l i z e RecommendationsDocuments M L S E R V I C E S (ML developers and data scientists) A m a z o n S a g e M a k e r G r o u n d T r u t h A l g o r i t h m s N o t e b o o k s M a r k e t p l a c e U n s u p e r v i s e d L e a r n i n g S u p e r v i s e d L e a r n i n g R e i n f o r c e m e n t L e a r n i n g O p t i m i z a t i o n ( N e o ) T r a i n i n g 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 (ML researchers and academics) Infrastructure A m a z o n E C 2 P 3 & P 3 D N A m a z o n E C 2 C 5 F P G A s A W S G r e e n g r a s s A m a z o n E l a s t i c I n f e r e n c e A m a z o n I n f e r e n t i a
- 7. The Amazon Machine Learning stack M L S E R V I C E S (ML developers and data scientists) A m a z o n S a g e M a k e r G r o u n d T r u t h A l g o r i t h m s N o t e b o o k s M a r k e t p l a c e U n s u p e r v i s e d L e a r n i n g S u p e r v i s e d L e a r n i n g R e i n f o r c e m e n t L e a r n i n g O p t i m i z a t i o n ( N e o ) T r a i n i n g
- 8. Amazon SageMaker Bringing machine learning to all developers C o l l e c t a n d p r e p a r e t r a i n i n g d a t a C h o o s e a n d o p t i m i z e y o u r M L a l g o r i t h m S e t u p a n d m a n a g e e n v i r o n m e n t s f o r t r a i n i n g Train and tune model (trial and error) Deploy model in production S c a l e a n d m a n a g e t h e p r o d u c t i o n e n v i r o n m e n t
- 9. Pre-built notebooks for common problems C o l l e c t a n d p r e p a r e t r a i n i n g d a t a C h o o s e a n d o p t i m i z e y o u r M L a l g o r i t h m S e t u p a n d m a n a g e e n v i r o n m e n t s f o r t r a i n i n g Train and tune model (trial and error) Deploy model in production S c a l e a n d m a n a g e t h e p r o d u c t i o n e n v i r o n m e n t Amazon SageMaker Bringing machine learning to all developers
- 10. Pre-built notebooks for common problems C o l l e c t a n d p r e p a r e t r a i n i n g d a t a Train and tune model (trial and error) Deploy model in production S c a l e a n d m a n a g e t h e p r o d u c t i o n e n v i r o n m e n t B u i l t - i n , h i g h p e r f o r m a n c e a l g o r i t h m s C h o o s e a n d o p t i m i z e y o u r M L a l g o r i t h m 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 Amazon SageMaker Bringing machine learning to all developers
- 11. Pre-built notebooks for common problems C o l l e c t a n d p r e p a r e t r a i n i n g d a t a Train and tune model (trial and error) Deploy model in production S c a l e a n d m a n a g e t h e p r o d u c t i o n e n v i r o n m e n t B u i l t - i n , h i g h p e r f o r m a n c e a l g o r i t h m s C h o o s e a n d o p t i m i z e y o u r M L a l g o r i t h m One-click training Set up and manage environments for training Amazon SageMaker Bringing machine learning to all developers
- 12. Pre-built notebooks for common problems C o l l e c t a n d p r e p a r e t r a i n i n g d a t a Deploy model in production S c a l e a n d m a n a g e t h e p r o d u c t i o n e n v i r o n m e n t B u i l t - i n , h i g h p e r f o r m a n c e a l g o r i t h m s C h o o s e a n d o p t i m i z e y o u r M L a l g o r i t h m One-click training Set up and manage environments for training O p t i m i z a t i o n Amazon SageMaker Bringing machine learning to all developers Train and tune model (trial and error)
- 13. Pre-built notebooks for common problems C o l l e c t a n d p r e p a r e t r a i n i n g d a t a S c a l e a n d m a n a g e t h e p r o d u c t i o n e n v i r o n m e n t B u i l t - i n , h i g h p e r f o r m a n c e a l g o r i t h m s C h o o s e a n d o p t i m i z e y o u r M L a l g o r i t h m One-click training Set up and manage environments for training O p t i m i z a t i o n One-click deployment Deploy model in production Amazon SageMaker Bringing machine learning to all developers Train and tune model (trial and error)
- 14. Amazon SageMaker Bringing machine learning to all developers Pre-built notebooks for common problems C o l l e c t a n d p r e p a r e t r a i n i n g d a t a B u i l t - i n , h i g h p e r f o r m a n c e a l g o r i t h m s C h o o s e a n d o p t i m i z e y o u r M L a l g o r i t h m One-click training Set up and manage environments for training O p t i m i z a t i o n F u l l y m a n a g e d w i t h a u t o - s c a l i n g , h e a l t h c h e c k s , a u t o m a t i c h a n d l i n g o f n o d e f a i l u r e s , a n d s e c u r i t y c h e c k s S c a l e a n d m a n a g e t h e p r o d u c t i o n e n v i r o n m e n t Train and tune model (trial and error) One-click deployment Deploy model in production
- 15. More than ten thousand customers using Amazon SageMaker
- 16. The Amazon Machine Learning stack A I S E R V I C E S (App developers with little knowledge of ML) A m a z o n R e k o g n i t i o n I m a g e A m a z o n P o l l y A m a z o n T r a n s c r i b e A m a z o n T r a n s l a t e A m a z o n C o m p r e h e n dA m a z o n L e x A m a z o n R e k o g n i t i o n V i d e o Vision Speech LanguageChatbots A m a z o n F o r e c a s t Forecasting A m a z o n T e x t r a c t A m a z o n P e r s o n a l i z e RecommendationsDocuments M L S E R V I C E S (ML developers and data scientists) A m a z o n S a g e M a k e r G r o u n d T r u t h A l g o r i t h m s N o t e b o o k s M a r k e t p l a c e U n s u p e r v i s e d L e a r n i n g S u p e r v i s e d L e a r n i n g R e i n f o r c e m e n t L e a r n i n g O p t i m i z a t i o n ( N e o ) T r a i n i n g 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 (ML researchers and academics) Infrastructure A m a z o n E C 2 P 3 & P 3 D N A m a z o n E C 2 C 5 F P G A s A W S G r e e n g r a s s A m a z o n E l a s t i c I n f e r e n c e A m a z o n I n f e r e n t i a
- 17. The Amazon Machine Learning stack A I S E R V I C E S (App developers with little knowledge of ML) A m a z o n R e k o g n i t i o n I m a g e A m a z o n P o l l y A m a z o n T r a n s c r i b e A m a z o n T r a n s l a t e A m a z o n C o m p r e h e n dA m a z o n L e x A m a z o n R e k o g n i t i o n V i d e o Vision Speech LanguageChatbots A m a z o n F o r e c a s t Forecasting A m a z o n T e x t r a c t A m a z o n P e r s o n a l i z e RecommendationsDocuments
- 18. How is Artificial Intelligence changing the world? MATÍAS BATTAGLIA SOLUTIONS ARCHITECT @_MattBattaglia mbattagliaromano [email protected]
- 20. About Us Nubiral is a boutique technology company, that focuses on product development and professional services for enterprises by adopting public, private and hybrid cloud methodologies. @_MattBattaglia mbattagliaromano [email protected]
- 21. @_MattBattaglia mbattagliaromano [email protected] How can we help you… DevOps Cloud BigData Analytics AI Optimization
- 22. @_MattBattaglia mbattagliaromano [email protected] How is Artificial Intelligence changing the world?
- 23. @_MattBattaglia mbattagliaromano [email protected] “The number of enterprises implementing artificial intelligence grew 270 percent in the past four years and tripled in the past year.” -- Gartner
- 24. @_MattBattaglia mbattagliaromano [email protected] How can Artificial Intelligence help your business
- 26. Smart Doorbell
- 31. @_MattBattaglia mbattagliaromano [email protected] A.I. is changing the world A.I. adoption is on the rise Innovation should be a priority A.I. enhances existing products KEY TAKEAWAYS…
- 32. THANK YOU! MATÍAS BATTAGLIA SOLUTIONS ARCHITECT @_MattBattaglia mbattagliaromano [email protected]
- 33. N o M L e x p e r i e n c e r e q u i r e d NEW! R e a l - t i m e p e r s o n a l i z a t i o n a n d r e c o m m e n d a t i o n s e r v i c e , b a s e d o n t h e s a m e t e c h n o l o g y u s e d a t A m a z o n . c o m A V A I L A B L E I N P R E V I E W T O D A Y Amazon Personalize
- 34. Activity stream from app Views, signups, conversion, etc. Inventory Articles, products, videos, etc. Demographics (optional) LOAD DATA (EMR Cluster) INSPECT DATA IDENTIFY FEATURES SELECT ALGORITHMS SELECT HYPERPARAMETERS TRAIN MODELS OPTIMIZE MODELS HOST MODELS BUILD FEATURE STORE CREATE REAL-TIME CACHES Customized personalization & recommendation API Fully managed by Amazon Personalize Amazon Personalize Amazon Personalize: machine learning personalization and recommendations Age, location, etc.
- 35. NEW! A c c u r a t e t i m e - s e r i e s f o r e c a s t i n g s e r v i c e , b a s e d o n t h e s a m e t e c h n o l o g y u s e d a t A m a z o n . c o m A V A I L A B L E I N P R E V I E W T O D A Y Amazon Forecast N o M L e x p e r i e n c e r e q u i r e d
- 36. Historical data Supply chain, inventory, etc. Customized forecasting API Inspect data Identify features Select from 8 algorithms Select hyperparameters Host models Load data Train models Optimize models Related “causal” data Weather, special offers, product details F u l l y m a n a g e d b y A m a z o n F o r e c a s t Amazon Forecast Amazon Forecast: machine learning time-series forecasting
- 37. Using Amazon Forecast for time-series forecasts Any historical time-series Integrates with SAP and Oracle Supply Chain Custom forecasts with 3 clicks 50% more accurate 1/10th the cost Integrates with Amazon Timestream Retail demand Travel demand AWS usage Revenue forecasts Web traffic Advertising demand Generate forecasts for:
- 38. The Amazon Machine Learning stack A I S E R V I C E S (App developers with little knowledge of ML) A m a z o n R e k o g n i t i o n I m a g e A m a z o n P o l l y A m a z o n T r a n s c r i b e A m a z o n T r a n s l a t e A m a z o n C o m p r e h e n dA m a z o n L e x A m a z o n R e k o g n i t i o n V i d e o Vision Speech LanguageChatbots A m a z o n F o r e c a s t Forecasting A m a z o n T e x t r a c t A m a z o n P e r s o n a l i z e RecommendationsDocuments M L S E R V I C E S (ML developers and data scientists) A m a z o n S a g e M a k e r G r o u n d T r u t h A l g o r i t h m s N o t e b o o k s M a r k e t p l a c e U n s u p e r v i s e d L e a r n i n g S u p e r v i s e d L e a r n i n g R e i n f o r c e m e n t L e a r n i n g O p t i m i z a t i o n ( N e o ) T r a i n i n g 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 (ML researchers and academics) Infrastructure A m a z o n E C 2 P 3 & P 3 D N A m a z o n E C 2 C 5 F P G A s A W S G r e e n g r a s s A m a z o n E l a s t i c I n f e r e n c e A m a z o n I n f e r e n t i a
- 39. Zona Demo: Face detection architecture