Machine Learning with Amazon SageMaker
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The document discusses Amazon SageMaker, a fully managed machine learning service. It provides an overview of SageMaker's capabilities for preparing, building, training and deploying machine learning models. Key features highlighted include SageMaker Studio for an integrated development environment, Autopilot for automatic model creation, JumpStart for pre-built solutions, and Data Wrangler for preparing data. Use cases and demos are presented to illustrate how customers can use SageMaker's services and features to develop machine learning applications.
Machine Learning with Amazon SageMaker
- 1. 1 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | 1 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Machine learning for every data scientist and developer Vladimír Šimek Sr. Solutions Architect, AWS Machine Learning with Amazon SageMaker AWS Česko-Slovenský Webinár 02/2021
- 2. 2 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Agenda • Gentle introduction • AI/ML on AWS – the full stack • Introduction to Amazon SageMaker • Use Cases • Demos • Resources • Q&A in chat window
- 3. 3 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | The AWS ML Stack Broadest and most complete set of machine learning capabilities Amazon SageMaker VISION SPEECH TEXT SEARCH CHATBOTS PERSONALIZATION FORECASTING FRAUD CONTACT CENTERS Deep Learning AMIs & Containers GPUs & CPUs Elastic Inference Trainium Inferentia FPGA AI SERVICES ML SERVICES FRAMEWORKS & INFRASTRUCTURE DeepGraphLibrary Amazon Rekognition Amazon Polly Amazon Transcribe +Medical Amazon Lex Amazon Personalize Amazon Forecast Amazon Comprehend +Medical Amazon Textract Amazon Kendra Amazon CodeGuru Amazon Fraud Detector Amazon Translate INDUSTRIAL AI CODE AND DEVOPS NEW Amazon DevOps Guru Voice ID For Amazon Connect Contact Lens NEW Amazon Monitron NEW AWS Panorama + Appliance NEW Amazon Lookout for Vision NEW Amazon Lookout for Equipment NEW Amazon HealthLake HEALTH AI NEW Amazon Lookout for Metrics ANOMALY DETECTION Amazon Transcribe for Medical Amazon Comprehend for Medical Label data NEW Aggregate & prepare data NEW Store & share features Auto ML Spark/R NEW Detect bias Visualize in notebooks Pick algorithm Train models Tune parameters NEW Debug & profile Deploy in production Manage & monitor NEW CI/CD Human review NEW: Model management for edge devices NEW: SageMaker JumpStart SAGEMAKER STUDIO IDE
- 4. 4 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Machine learning development is complex and costly Visualize in notebooks Pick algorithm Train models Tune parameters Deploy in production Manage and monitor Label data Collect and prepare data Store features CI/CD Check for bias
- 5. 5 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | https://aws.amazon.com/sagemaker Amazon SageMaker Most complete, end-to-end ML service Integrated Workbench Capabilities designed specifically for ML, data preparation, experiment management, and workflows Managed Infrastructure Designed for ultra low latency and high throughput, automatic scaling, and distributed training Managed Tooling Purpose-built from the ground up to work together including auto ML, collaboration, debugger, profiler, bias analyzer, and explainability
- 6. 6 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker overview PREPARE SageMaker Ground Truth Label training data for machine learning SageMaker Data Wrangler NEW Aggregate and prepare data for machine learning SageMaker Processing Built-in Python, BYO R/Spark SageMaker Feature Store NEW Store, update, retrieve, and share features SageMaker Clarify NEW Detect bias and understand model predictions BUILD SageMaker Studio Notebooks Jupyter notebooks with elastic compute and sharing Built-in and Bring your-own Algorithms Dozens of optimized algorithms or bring your own Local Mode Test and prototype on your local machine SageMaker Autopilot Automatically create machine learning models with full visibility SageMaker JumpStart NEW Pre-built solutions for common use cases TRAIN & TUNE Managed Training Distributed infrastructure management SageMaker Experiments Capture, organize, and compare every step Automatic Model Tuning Hyperparameter optimization Distributed Training Libraries NEW Training for large datasets and models SageMaker Debugger NEW Debug and profile training runs Managed Spot Training Reduce training cost by 90% DEPLOY & MANAGE Managed Deployment Fully managed, ultra low latency, high throughput Kubernetes & Kubeflow Integration Simplify Kubernetes-based machine learning Multi-Model Endpoints Reduce cost by hosting multiple models per instance SageMaker Model Monitor Maintain accuracy of deployed models SageMaker Edge Manager NEW Manage and monitor models on edge devices SageMaker Pipelines NEW Workflow orchestration and automation Amazon SageMaker SageMaker Studio Integrated development environment (IDE) for ML
- 7. 7 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Tens of thousands of customers use Amazon SageMaker
- 8. 8 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | SageMaker Common use cases Demand Forecasting Retail, Consumer Goods, Manufacturing Extract and Analyze Data from Documents Healthcare, Legal, Media/Ent, Education Computer Vision Healthcare, Pharma, Manufacturing Autonomous Driving Automotive, Transportation Personalized Recommendations Media & Entertainment, Retail, Education Churn Prediction Retail, Education, Software & Internet Predictive Maintenance Manufacturing, Automotive, IoT Fraud Detection Financial Services, Online Retail Credit Risk Prediction Financial Services, Retail
- 9. 9 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker Features Amazon SageMaker Studio Amazon SageMaker Autopilot Amazon SageMaker JumpStart Amazon SageMaker Pipelines Amazon SageMaker Clarify PREPARE DATA Amazon SageMaker Ground Truth Amazon SageMaker Processing Amazon SageMaker Data Wrangler Amazon SageMaker Feature Store TRAIN Managed Training Amazon SageMaker Experiments Amazon SageMaker distributed training libraries Amazon SageMaker Debugger DEPLOY Managed Deployment Amazon SageMaker Edge Manager OTHER Kubernetes integration Security Human reviews
- 10. 10 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | 10 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker Studio
- 11. 11 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker Studio Fully Integrated Development Environment (IDE) for machine learning Collaboration at scale Share notebooks without tracking code dependencies Easy experiment management Organize, track, and compare thousands of experiments Automatic model generation Get accurate models with full visibility and control without writing code Higher quality ML models Automatically debug errors, monitor models, and maintain high quality Increased productivity Code, build, train, deploy, and monitor in a unified visual interface
- 12. 12 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Use Amazon SageMaker Studio to update models and see impact on model quality immediately
- 13. 13 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker Notebooks Fast-start sharable notebooks Easy access with Single Sign-On (SSO) Access your notebooks in seconds Fully managed and secure Administrators manage access and permissions Fast setup Start your notebooks without spinning up compute resources Easy collaboration Share notebooks with a single click Flexible Dial up or down compute resources (coming soon)
- 14. 14 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Use Amazon SageMaker Notebooks to easily share your work with colleagues
- 15. 15 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Code dependencies are automatically captured to enable collaboration with colleagues
- 16. 16 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker Autopilot Automatic model creation with full visibility and control Quick to start Provide your data in a tabular form and specify target prediction Automatic model creation Get ML models with feature engineering and model tuning automatically done Visibility and control Get notebooks for your models with source code Recommendations and optimization Get a leaderboard and continue to improve your model
- 17. 17 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Use Amazon SageMaker Autopilot to automatically train and tune the best machine learning models
- 18. 18 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | 18 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Demo #1
- 19. 19 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | 19 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker JumpStart
- 20. 20 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Getting started with machine learning can be challenging Requires knowledge of cloud infrastructure Time consuming Multiple steps involved with building, training, and deploying ML models
- 21. 21 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | SageMaker JumpStart Easily and quickly bring machine learning applications to market Solutions can be used out-of-the-box or can be customized for a specific business problem 15+ pre-built solutions for common ML use cases Use one-click deployable ML models and algorithms from popular model zoos Accelerate time to deploy over 150 open source models Easily bring ML applications to market using pre-built solutions, ML models, and algorithms from popular model zoos, and getting started content Get started with just a few clicks
- 22. 22 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | SageMaker JumpStart Use cases Autonomous driving Churn prediction Computer vision Credit risk prediction Demand forecasting Extract data from documents Fraud detection Personalized recommendations Predictive maintenance
- 23. 23 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | 23 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker Data Wrangler
- 24. 24 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | 80% of time spent on data prep Source: Forbes survey of 80 data scientists, March 2016 60% 19% 9% 5% 4% 3% Cleaning and organizing data Collecting data sets Mining data for patterns Other Refining algorithms Building training sets What data scientists spend the most time doing
- 25. 25 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker Data Wrangler The fastest and easiest way to prepare data for machine learning 25 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved |
- 26. 26 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | SageMaker Data Wrangler Use cases Cleanse & Explore Data Use built-in data transforms to accelerate data cleansing and exploration Visualize & Understand Data Enrich Data Quickly detect outliers or extreme values within a data set without the need to write code Use pre-configured data transformation tools to transform data into formats that can be used to build accurate ML models
- 27. 27 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Quickly select and query data Select data from Amazon Athena, Amazon Redshift, AWS Lake Formation, Amazon S3, and features from SageMaker Feature Store Write queries for data sources before importing data over to SageMaker Data Wrangler Import data in various file formats, such as CSV files, parquet files, and database tables directly into Amazon SageMaker
- 28. 28 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Easily transform data Transform your data without writing a single line of code using pre-configured data transforms Preconfigured data transforms include convert column type, rename column, and delete column Author custom transforms in PySpark, SQL, and Pandas Detect bias and identify dataset imbalance with SageMaker Clarify
- 29. 29 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Understand your data visually Intuitively understand your data with a set of pre-configured visualization templates Preconfigured visualization templates include histograms, scatter plots, box and whisker plots, line plots, and bar charts Interactively create and edit your own visualizations so you can quickly detect outliers or extreme values
- 30. 30 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Quickly estimate model accuracy Identify inconsistencies in data preparation workflows and diagnose issues before ML models are deployed into production Select subsets of data to identify errors Identify which features are contributing to model performance relative to others Determine if additional feature engineering is needed to improve model performance
- 31. 31 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Deploy data preparation workflows into production Export data preparation workflows to a notebook or Python code Integrate your workflow with SageMaker Pipelines to automate model deployment and management Publish created features to SageMaker Feature Store for reuse and syndication across teams and projects
- 32. 32 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | 32 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Demo #2
- 33. 33 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker is devops ready Security features to help you meet strict security requirements of ML workloads Security PCI, HIPAA, SOC 1/2/3, FedRAMP, and ISO 9001/27001/27017/27018 Compliance Create automated workflows in minutes to support thousands of models ML workflows Train complex models with massive datasets Scalability Automatic scheduling and execution of jobs with managed infrastructure Orchestration
- 34. 34 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker integrates with Kubernetes Amazon SageMaker Operators for Kubernetes 2 Amazon SageMaker Components for Kubeflow Pipelines 1 Pipelines
- 35. 35 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Amazon SageMaker Built-in features help you go from idea to production faster, without compromising security Control data traffic across SageMaker components over a private network, and ensure appropriate ingress/egress with single-tenancy Infrastructure and network isolation Define, enforce, and audit who can be authenticated and authorized to use Amazon SageMaker resources Authentication and authorization Ensure automatic data encryption at rest and in transit with flexibility to bring your own keys Data protection Track, trace, and audit all API calls, events, data access, or interactions down to the user and IP level to ensure quick remediation Auditability and monitoring Inherit the most comprehensive compliance controls, and easily abide by your industry’s legislation Compliance certifications
- 36. 36 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Resources https://aws.amazon.com/sagemaker/ https://aws.amazon.com/sagemaker/getting-started/ https://www.aws.training/ https://github.com/aws/amazon-sagemaker-examples https://www.getstartedonsagemaker.com/ https://aws.amazon.com/free/
- 37. 37 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | 37 © 2020 Amazon Web Services, Inc. or its affiliates. All rights reserved | Thank you [email protected]