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LinkedIn Learning

Learning XAI: Explainable Artificial Intelligence

via LinkedIn Learning

Overview

Learn how explainable artificial intelligence (XAI) works and how it will impact data science-related projects and businesses.

Syllabus

Introduction
  • Explainable AI: Expanding the frontiers of artificial intelligence
  • Introduction to AI and ML
1. Explainable AI (XAI)
  • What is XAI?
  • XAI techniques
  • The need for XAI: Business
  • The need for XAI: Legal
  • Limitations of XAI
2. Humans and Machines Have Different Strengths and Weaknesses
  • Humans are better at some things
  • Computers are better at some things
3. The Case for Human Machine Collaboration
  • Combining the strengths of humans and machines
  • Example: Centaur chess
4. Examples of Possible XAI Applications
  • Simple example: Driving directions
  • Medical example: Explainability for surgical health care and medicine
  • Business example 1: Marketing
  • Business example 2: Fraud detection
5. Next Steps
  • Full adoption will take time
  • Invest in XAI
Conclusion
  • Summary

Taught by

Aki Ohashi

Reviews

4.7 rating at LinkedIn Learning based on 140 ratings

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