Table of contents
Introduction
17m 6s
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Course Introduction | 3m 43s
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How to Follow Along with Demos in This Course | 13m 23s
Machine Learning on AWS: Tools and Services
1h 17m 44s
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Section Introduction | 9m 50s
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SageMaker Canvas Overview | 2m 58s
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Setting Up SageMaker Canvas | 4m 45s
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Running Predictions in SageMaker Canvas | 14m 9s
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SageMaker Studio Lab Overview | 2m 36s
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Setting Up a SageMaker Studio Lab Account | 6m 35s
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Exploring the SageMaker Studio Lab Examples | 7m 46s
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SageMaker Studio Overview | 2m 41s
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Setting Up SageMaker Studio for Course Demos | 9m 34s
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Section Summary | 1m 50s
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Quiz: Machine Learning on AWS: Tools and ServicesQuiz: Machine Learning on AWS: Tools and Services | 15m
Preparing Data with SageMaker Data Wrangler and Feature Store
1h 32m 30s
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Section Introduction | 4m 31s
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Importing Data into Data Wrangler | 13m 48s
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Analyzing and Visualizing Data in Data Wrangler | 12m 34s
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Transforming Data in Data Wrangler | 14m 56s
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Exporting Data for Training | 10m 59s
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Working with the SageMaker Feature Store | 4m 40s
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Ingesting and Accessing Features in SageMaker Feature Store | 15m 1s
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Section Summary | 1m 1s
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Quiz: Preparing Data with SageMaker Data Wrangler and Feature StoreQuiz: Preparing Data with SageMaker Data Wrangler and Feature Store | 15m
Building and Training Models with SageMaker Studio
1h 30m 14s
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Section Introduction | 2m 54s
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Using SageMaker's Built-In Algorithms | 9m 17s
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SageMaker's Algorithms in Action | 15m 1s
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Using Popular Frameworks | 5m 42s
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Working in Script Mode with a Framework | 9m 46s
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Using SageMaker Experiments to Manage Training Jobs | 11m 5s
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Detecting Bias with SageMaker Clarify | 13m 10s
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Using SageMaker for Collaboration | 6m 11s
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Section Summary | 2m 8s
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Quiz: Building and Training Models with SageMaker StudioQuiz: Building and Training Models with SageMaker Studio | 15m
Deployment and Inference with SageMaker Studio
42m 24s
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Section Introduction | 3m 4s
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Working with SageMaker Batch Transform | 8m 2s
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Hosting Real-Time Endpoints for Live Inference | 9m 22s
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Optimizing Machine Learning Deployments | 5m 36s
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Section Summary | 1m 20s
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Quiz: Deployment and Inference with SageMaker StudioQuiz: Deployment and Inference with SageMaker Studio | 15m
Security Best Practices for Machine Learning on AWS
48m 32s
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Section Introduction | 2m 51s
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Securing Your Resources in a VPC | 5m 8s
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Using the Principle of Least Privilege | 4m 11s
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Encrypting Data at Rest and in Transit | 8m 12s
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Protecting Credentials with Secrets Manager | 3m 28s
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Monitoring Model Input and Output | 1m 19s
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Enabling Logging for Model Access | 2m 55s
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Using Version Control on Model Artifacts | 3m 39s
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Section Summary | 1m 49s
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Quiz: Security Best Practices for Machine Learning on AWSQuiz: Security Best Practices for Machine Learning on AWS | 15m
Conclusion
7m 2s
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Course Summary | 4m 56s
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Conclusion and What's Next | 2m 6s
About the author
Amber Israelsen
Amber has been a software developer and technical trainer since the early 2000s. She holds certifications for AWS and a variety of Microsoft technologies. She also focuses on user experience and professional skills training, bridging the gap between techies and non-techies.
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