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DataXDay - Machine learning models at scale with Amazon SageMaker

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Build, train, and deploy machine learning models at scale

Machine learning often feels a lot harder than it should be to most developers because the process to build and train models, and then deploy them into production is too complicated and too slow.

Amazon SageMaker includes modules that can be used together or independently to build, train, and deploy your machine learning models.

Olivier Bergeret - AWS
https://dataxday.fr/

Video available: https://www.youtube.com/watch?v=3eV4x_GR_f8

Published in: Technology
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DataXDay - Machine learning models at scale with Amazon SageMaker

  1. 1. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Machine learning models at scale with Amazon SageMaker Olivier Bergeret, Solutions Architect mgr, AWS
  2. 2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Fulfilment & Logistics At Amazon, we’ve been making investments in ML for the last 20 years…
  3. 3. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
  4. 4. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. At Amazon, we’ve been making investments in ML for the last 20 years… Fulfilment & Logistics Search & Discovery
  5. 5. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
  6. 6. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. At Amazon, we’ve been making investments in ML for the last 20 years… Fulfilment & Logistics Existing Products Search & Discovery
  7. 7. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
  8. 8. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Fulfilment & Logistics Existing Products New Products Search & Discovery At Amazon, we’ve been making investments in ML for the last 20 years…
  9. 9. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
  10. 10. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
  11. 11. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
  12. 12. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Put machine learning in the hands of every developer and data scientist ML @ AWS: Our mission
  13. 13. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. The AWS Machine Learning Stack Application Services Platform Services Frameworks Infrastructure Vision Rekognition Image Rekognition Video Language Lex Translate Comprehend Speech Polly Transcribe Amazon SageMaker AWS DeepLens Amazon Machine Learning Amazon EMR Spark Amazon Mechanical Turk AWS Deep Learning AMI TensorFlow Apache MXNet Gluon Cognitive Toolkit Caffe Keras PyTorch Chainer Compute GPU - P3 IoT - Greengrass Inference Mobile
  14. 14. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Rekognition Object, Scene & Activity Recognition Facial Recognition Facial Analysis Person 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
  15. 15. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. 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
  16. 16. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon EC2 P3 Instances • Up to eight NVIDIA Tesla V100 GPUs • 1 PetaFLOP of computational performance – 14x better than P2 • 300 GB/s GPU-to-GPU communication (NVLink) – 9X better than P2 • 16 GB GPU memory with 900 GB/sec peak GPU memory bandwidth T h e f a s t e s t , m o s t p o w e r f u l G P U i n s t a n c e s i n t h e c l o u d
  17. 17. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. • Get started quickly with easy-to-launch tutorials • Hassle-free setup and configuration • Pay only for what you use – no additional charge for the AMI • Accelerate your model training and deployment • Support for popular deep learning frameworks AWS Deep Learning AMI
  18. 18. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. CUSTOMERS RUNNING MACHINE LEARNING ON AWS TODAY
  19. 19. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon SageMaker A managed service that provides the quickest and easiest way for data scientists and developers to get ML models from idea to production.
  20. 20. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon’s fast, scalable algorithms Idiomatic, distributed TensorFlow & MXNet Bring your own algorithm Hyperparameter optimization UX HostingTraining Amazon SageMaker Components
  21. 21. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon’s fast, scalable algorithms Idiomatic, distributed TensorFlow & MXNet Bring your own algorithm Hyperparameter optimization UX HostingTraining Amazon SageMaker Components
  22. 22. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Or Apache Spark through Amazon EMR and the SageMaker Spark SDK UX Use the SageMaker hosted notebook instances Or the SageMaker console for a point-and-click experience Or your own device (EC2, laptop, etc.)
  23. 23. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon’s fast, scalable algorithms Idiomatic, distributed TensorFlow & MXNet Bring your own algorithm Hyperparameter optimization UX HostingTraining Amazon SageMaker Components
  24. 24. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. No setup Training Streaming datasets and distributed compute Docker / Amazon ECS Deploy trained models locally or to SageMaker, AWS Greengrass, or DeepLens
  25. 25. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon’s fast, scalable algorithms Idiomatic, distributed TensorFlow & MXNet Bring your own algorithm Hyperparameter optimization UX HostingTraining Amazon SageMaker Components
  26. 26. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. One-step deployment Low latency, high throughput, and high reliability A/B testing Use your own model Hosting
  27. 27. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon’s fast, scalable algorithms Idiomatic, distributed TensorFlow & MXNet Bring your own algorithm Hyperparameter optimization UX HostingTraining Amazon SageMaker Components
  28. 28. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. XGBoost, FM, linear, and forecasting for supervised learning Kmeans, PCA, and Word2Vec for clustering and preprocessing Image classification with convolutional neural networks LDA and NTM for topic modeling; seq2seq for translation Built-in Algorithms
  29. 29. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon’s fast, scalable algorithms Idiomatic, distributed TensorFlow & MXNet Bring your own algorithm Hyperparameter optimization UX HostingTraining Amazon SageMaker Components
  30. 30. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Explore and refine models in a single notebook instance TensorFlow & MXNet Containers Deploy to production Sample your data Use the same code to train on the full dataset in a cluster of GPU instances
  31. 31. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon’s fast, scalable algorithms Idiomatic, distributed TensorFlow & MXNet Bring your own algorithm Hyperparameter optimization UX HostingTraining Amazon SageMaker Components
  32. 32. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Bring Your Own Algorithm Add algorithm code to a Docker container Choose your preferred framework Publish to Amazon ECS Amazon ECS
  33. 33. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Amazon’s fast, scalable algorithms Idiomatic, distributed TensorFlow & MXNet Bring your own algorithm Hyperparameter optimization UX HostingTraining Amazon SageMaker Components
  34. 34. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Hyperparameter Optimization Run a large set of training jobs with varying hyperparameters Then search the hyperparameter space for improved accuracy
  35. 35. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Resize as you need Common tools pre-installed Easy access to your data sources No servers to manage No Setup for Data Exploration
  36. 36. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. M o d u l a r A r c h i t e c t u r e – U s e W h a t Y o u N e e d Past data Training algorithm Model artifacts Inference code Client application Model Data Inference Ground truth Amazon SageMaker
  37. 37. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. ML compute by the second, starting at $0.0464/hr. ML storage by the second, at $0.14 per GB-month Data processed in notebooks and hosting, at $0.016 per GB Free trial to quickly get started Pay as You Go – Inexpensive
  38. 38. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. How do I get started using Amazon SageMaker?
  39. 39. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Start with Notebook Samples
  40. 40. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Modify to Access Your Data Sources
  41. 41. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Train Your Model
  42. 42. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Deploy Your Model
  43. 43. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved. Perform Inferences
  44. 44. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Demo Part 1: Start Training and Deployment
  45. 45. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Demo Part 2: Evaluate deployed model
  46. 46. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. THANK YOU!
  47. 47. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

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