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Debiasing AI Using Amazon SageMaker

Offered By: LinkedIn Learning

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Amazon SageMaker Courses Fairness in AI Courses Machine Learning Models Courses

Course Description

Overview

Learn how to debias AI with Amazon SageMaker. Build machine learning models that are fair, transparent, and explainable.

Syllabus

Introduction
  • Debiasing AI using Amazon SageMaker
  • What you should know
1. Crime-Fighting Case Study
  • Predictive policing
  • Overview of crime-fighting case study
  • Architecture diagram
  • Tools, services, and costs
  • Terms and concepts
  • Demo of Amazon SageMaker
2. Building the Model via SageMaker
  • What is SageMaker?
  • Machine learning process
  • Inspect and visualize data
  • Prepare the data
  • Train the model
  • Deploy the model
3. Deploying and Testing the Model via DeepLens
  • What is DeepLens?
  • Deploy model to AWS DeepLens
  • Extend AWS DeepLens
  • Retrieve attributes via AWS Rekognition
  • Invoke the crime model
  • Set up model alerts
4. Explaining the Model
  • What is explainable AI (XAI)?
  • Trust and transparency issues
  • Making algorithms explainable
Conclusion
  • Next steps

Taught by

Kesha Williams

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