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Building Trusted AI Products - Workshop
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- 1 Introduction
- 2 What is the Pear Guide Book
- 3 Chapter Updates
- 4 Case Studies
- 5 Workshop Resources
- 6 User Need
- 7 Patterns
- 8 Early good data practices
- 9 Embrace noisy data
- 10 Maintain the data set
- 11 Create realistic data
- 12 Recommendations course
- 13 Recommendation Systems course
- 14 User Experience
- 15 Design Patterns
- 16 Setting the right expectations
- 17 Explaining the benefits
- 18 Explaining recommendations
- 19 Recap
- 20 Model Confidence
- 21 Errors
- 22 Examples of errors
- 23 Let users give feedback
- 24 What action will be taken
- 25 Example
- 26 Summary