[NEW LAUNCH!] Accelerating Machine Learning with Amazon SageMaker and AWS Marketplace (AIM371) - AWS re:Invent 2018
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Until now, many customers spent time creating or searching for the right algorithm and model when using Amazon SageMaker. In this session you’ll learn how to build machine learning applications even faster by finding curated algorithms and model packages in AWS Marketplace and deploying them directly on Amazon SageMaker.
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[NEW LAUNCH!] Accelerating Machine Learning with Amazon SageMaker and AWS Marketplace (AIM371) - AWS re:Invent 2018
- 2. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. New:Accelerating Machine Learning withAmazonSageMaker andAWS Marketplace Garth Fort Director Product Management AWS Marketplace K E M 2 4 Srini Sankaran Senior Product Manager AWS Marketplace
- 3. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 4. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS Marketplacesimplifiessoftwareprovisioning FIND, TEST, BUY, AND DEPLOY SOFTWARE IN THE CLOUD • Deploy software on demand • Procure new, Bring Your Own License, or free open source • Tagged, trackable, and metered • 1,300+ participating ISVs • 4,200+ product listings • 200,000 active customers • Deployed in 16 regions • Offers 35 categories • Over 570 million hours of EC2 deployed monthly
- 5. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. + AMI AMI CFT SaaS IoT WAF NEW Amazon SageMaker Containers New:Machinelearning
- 6. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. AmazonSageMaker Fully managed hosting with automatic scaling One-click deployment Pre-built notebooks for common problems Built-in, high- performance algorithms One-click training Automatic Model tuning BUILD TRAIN DEPLOY
- 7. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. AmazonSageMakercustomers
- 8. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Discover over a 150 trusted, curated, ML algorithms, and model packages 53 machine learning categories 14 industry segments 30+ launch partners 9 preview customers Free | Free trial | Paid licensing types Machine learning (ML) algorithms and models
- 9. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. BUY: (ENTERPRISE CUSTOMERS) Browse and search algorithms/models from Amazon SageMaker Procure and manage your products on AWS Marketplace SELL: (SOFTWARE VENDORS/START- UPS/INDUSTRY/ACADEMICS) Package and upload your algorithms/models as Docker images using AWS SDKs on Amazon SageMaker List and publish your algorithms/models on AWS Marketplace Reduce time and cost tied to marketing and scaling your products Buy and sellalgorithmsand pretrained models packages forAmazonSageMaker
- 10. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Whatweheardfrom our customers R EIN VEN TIN G TH E W H EEL Significant time and valuable resources are spent in developing ML solutions to problems that are already solved by others POOR SELEC TION It is hard to find, evaluate, and qualify trust-worthy algorithms and models for enterprise use cases LOST OPPOR TU N ITY Difficulty in deployment, version management, and reproducibility led to delay in time to market LA C K OF D ATA /IP SEC U R ITY No way to ensure data security, compliance needs, or regulatory standards for customer’s data and intellectual property
- 11. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Delivering valuetoyour customers faster Rapid deployment on Amazon SageMaker in minutes Tune your algorithms and models to your need Framework-agnostic deployment Easy version management and reproducibility Avoid undifferentiated heavy lifting Faster experimentation leads to more data science projects and research breakthroughs completed faster Highly secure deployment model for your data “ ” Accelerate delivery machine learning applications from weeks to days
- 12. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Whatcan youbuy? Algorithms let you train a custom model using your own data; you can also tune your algorithm using hyperparameters Model packages are pretrained by your seller and ready-to-use; you can run an inference in real-time or batch mode
- 13. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Machinelearning algorithm/model pricing and licensing Hourly Free trials Free Metered Paid $
- 14. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Pricing details Training price for algorithms Model package: Real-time inference price Model package: Batch inference price Algorithms: Amazon SageMaker, storage costs, notebook server Model Package: Amazon SageMaker, storage costs, data in/out charges +
- 15. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 16. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Optimus Primebuyer experience 1 2 3 Discover algorithms/ model packages AWS Marketplace Subscribe and configure your product in AWS Marketplace/ Amazon SageMaker Deploy on Amazon SageMaker
- 17. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Insurance industry: The fender bender use case Automating fraud check on insurance claims • Validate claim information (text/data) • Fraudulent activity prediction based on behavioral/historical data (data/structured) • Validating information submitted (images, accident reports)
- 18. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Sellersat launch
- 19. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Previewcustomers
- 20. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Machine Learning https://aws.amazon.com/marketplace /solutions/machinelearning
- 21. Thank you! © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Garth Fort fortgart@amazon.com Srini Sankaran srinisan@amazon.com
- 22. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 23. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 24. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 25. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
- 26. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. AWS Marketplace – Machine Learning Tune your algorithms and models to your need Rapidly deploy on Amazon SageMaker in minutes Experiment faster and reduce your time to market Scalable, highly secure deployment model Framework agnostic deployment Discover over a hundred trusted, curated, ML algorithms and model packages
- 27. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Whatdo customers reallywant? Faster time to market Simple pricing $ Global footprintAbility to configure and customize Experiment faster Secure, trusted, and curated product catalog Try-before-buy Quick, reproducible deployment
- 28. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Buyer experience Find Computer Vision Natural Language Processing Speech Recognition Text Image Video Audio Structured From a breadth of categories: Buy Free trial Free Pay-as-you-go Hourly Through flexible pricing options: Deploy Amazon SageMaker console Jupyter Notebook Amazon SageMaker SDK AWS CLI With multiple deployment options:
Hinweis der Redaktion
- AWS Marketplace provides over 4,200 software solutions from more than 1,300 ISVs and continues to grow and help customers migrate to the cloud. Today, customers are deploying over 570 million hours of EC2 monthly. If you do the math, that’s about 848K hours being deployed just in this hour.
- We have added various product types to AWS Marketplace over the years and are constantly expanding the selection for our customers. Last year we have added Web Application Firewall products to our selection. This year, we have added two new fulfillment types. We have added containers, which was launched on 11/27 and Andy launched algorithms and models for Amazon SageMaker on 11/28 via keynote.
- Amazon SageMaker is a fully managed service that removes the heavy lifting, complexity, and guesswork from each step of the machine learning process, empowering everyday developers and scientists to use machine learning much more expansively and successfully.
- Tens of thousands of customers are using AWS machine learning services, with active users increasing more than 250 percent in the last year, spurred by the broad adoption of Amazon SageMaker since AWS re: Invent 2017.
- AWS Machine Learning (ML) Marketplace lets customers browse and search over a hundred and fifty third-party ML algorithms and models from a broad range of categories such as computer vision, natural language processing, speech recognition, text, data, voice, image, video analysis, fraud detection, predictive analysis, and more. It also includes industry-specific ML products (such as demand forecasting, predicting engagement, etc.) for the financial services, healthcare, media and entertainment, oil and gas, information technology, manufacturing, and telecom industries.
- As a buyer you can review product descriptions, usage instructions, customer reviews, sample Jupyter notebooks, pricing, and support information. Deploy models with a few clicks directly from the Amazon SageMaker console, through a Jupyter notebook, or with the Amazon SageMaker SDK or AWS Command Line Interface (AWS CLI). You also have an option to monetize your IP as a seller. Sharing/monetizing your work is straightforward. You can bring in your algorithms/models packaged in Docker containers, create algorithm/model package entities on Amazon SageMaker, and list them in AWS Marketplace through a self service process.
- Many customers spent a lot of time solving problems that had already been solved. They developed models and algorithms as solutions to problems without realizing that someone else had already developed similar solutions If developers wanted to incorporate ready-to-use algorithms and models in their applications, they had to spend a lot of time searching for, and evaluating, the algorithms and models they found on the internet. When sourcing ML products it was hard to determine if it is secure and compliant with the regulatory needs of the customer. If a model is found to potentially meet a business need, it is hard to test and deploy. Customers spent 2-4 weeks just in deploying and configuring their algorithms and models.
- If you looking to build a custom model, you can start with an algorithm, create a training job with your own data, and build the model that suits your needs. If you are looking for a pretrained model, you can start with a model package, which enables you to hit the ground running.
- Algorithm and model package price consists of an hourly usage fee set by the seller and an infrastructure fee billed per hour based on the Amazon SageMaker resource usage There is a training price for the algorithm and an inference price for the model derived from the algorithm Customers pay the training price when they train a model using the seller's algorithm To run inference (prediction) with the model, customers use the seller’s inference image and pay the inference price. When buying model packages, customers will see only the inference price. For free products or products in free-trial offers, customers will be charged only for Amazon SageMaker resource usage
- Discover an algorithm or model package. Customers can browse and search for ML algorithms and model packages on the AWS Marketplace website. They can refine their search results by applying resource type, category, and pricing filters. From search results, they can access the product detail page, which allows them to review the product description, usage instructions, customer reviews, data requirements, sample Jupyter notebooks, and pricing and support information. Subscribe to an algorithm or model package and configure it. To view the procurement page, from the product detail page, choose Continue to subscribe. After reviewing the product pricing information and the End User License Agreement (EULA), the customer can subscribe. After subscribing, they can configure the product (for example, by selecting a specific version or deployment region) on the AWS Marketplace website. Deploy on Amazon SageMaker. After configuring the product, customers can view the Amazon SageMaker product detail page by choosing View in Amazon SageMaker. From the Amazon SageMaker console, they can deploy the algorithms and model packages using the Amazon SageMaker console, Jupyter notebook, Amazon SageMaker CLI commands, or APIs.
- Selected logo board of sellers signed up so far
- AWS Machine Learning (ML) Marketplace lets customers browse and search over a hundred third-party ML algorithms and models from a broad range of categories such as computer vision, natural language processing, speech recognition, text, data, voice, image, video analysis, fraud detection, predictive analysis, and more. It also includes industry-specific ML products (such as demand forecasting, predicting engagement, etc.) for the financial services, healthcare, media and entertainment, oil and gas, information technology, manufacturing, and telecom industries.
- Discover an algorithm or model package. Customers can browse and search for ML algorithms and model packages on the AWS Marketplace website. They can refine their search results by applying resource type, category, and pricing filters. From search results, they can access the product detail page, which allows them to review the product description, usage instructions, customer reviews, data requirements, sample Jupyter notebooks, and pricing and support information. Subscribe to an algorithm or model package and configure it. To view the procurement page, from the product detail page, choose Continue to subscribe. After reviewing the product pricing information and the End User License Agreement (EULA), the customer can subscribe. After subscribing, they can configure the product (for example, by selecting a specific version or deployment region) on the AWS Marketplace website. Deploy on Amazon SageMaker. After configuring the product, customers can view the Amazon SageMaker product detail page by choosing View in Amazon SageMaker. From the Amazon SageMaker console, they can deploy the algorithms and model packages using the Amazon SageMaker console, Jupyter notebook, Amazon SageMaker CLI commands, or APIs.