Extending Amazon Machine Learning

Amazon ML 2020
  • 15 Videos | 1h 7m 48s
  • Includes Assessment
  • Earns a Badge
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The Amazon Machine Learning framework allows you to quickly deploy machine learning models using Amazon Web Services, automate model deployment and maintenance, and configure other Amazon tools to work in synchronicity. AI practitioners should consider the benefits and best practices of working with Amazon ML and other Amazon services in their AI development projects. In this course, you'll explore advanced techniques for working with the Amazon ML framework. You'll examine the significant differences between Amazon ML and other frameworks. You'll recognize the advantages of using the Amazon ML platform for certain projects and identify the Amazon ML workflow. Finally, you'll complete a project developing and training an AI model using the Amazon ML framework, and troubleshoot typical problems that come up during model training and evaluation.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    specify cases in which it is advantageous to use Amazon ML over other platforms
    compare the use of Amazon ML and Google Cloud Platform
    compare the use of Amazon ML and Azure ML
    identify possible data sources for working with Amazon ML
    describe the capabilities of Amazon ML in relation to feature processing
    specify multiple approaches to how data can be split using Amazon ML
    list model types present in Amazon ML and specify their purposes
  • describe the process of batch prediction in Amazon ML and identify cases in which batch prediction is more desirable than online prediction
    describe how real-time prediction is made in Amazon ML
    troubleshoot common problems and identify approaches to improve model accuracy in Amazon ML
    describe Sagemaker requirements and problem to be solved
    demonstrate Sagemaker model training and validation
    validate the results of the Sagemaker model demo
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    3m 4s
    UP NEXT
  • Playable
    2. 
    Amazon ML vs. Other Platforms
    3m 9s
  • Locked
    3. 
    Amazon ML vs. Google Cloud Platform
    2m 48s
  • Locked
    4. 
    Amazon ML vs. Azure ML
    3m 8s
  • Locked
    5. 
    Data Sources in Amazon ML
    4m 10s
  • Locked
    6. 
    Feature Processing in Amazon ML
    3m 13s
  • Locked
    7. 
    Data Splitting in Amazon ML
    4m 7s
  • Locked
    8. 
    Amazon ML Model Types
    2m 47s
  • Locked
    9. 
    Batch Prediction in Amazon ML
    4m 36s
  • Locked
    10. 
    Real-time Prediction in Amazon ML
    5m 17s
  • Locked
    11. 
    Improving Model Accuracy in Amazon ML
    3m 45s
  • Locked
    12. 
    Introduction to Sagemaker
    8m 9s
  • Locked
    13. 
    Sagemaker Model Training and Validation
    10m 14s
  • Locked
    14. 
    Validating Sagemaker Model Results
    2m 4s
  • Locked
    15. 
    Course Summary
    49s

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