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Machine Learning for the 99%
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- 1 Introduction
- 2 State of AI
- 3 Cost of Training
- 4 Talent Shortage
- 5 Investments
- 6 AI Investments
- 7 Summary
- 8 Machine Learning Maturity
- 9 Machine Learning Product
- 10 Culture Data Infrastructure
- 11 Tech Unicorns
- 12 Culture
- 13 Training vs Reality
- 14 The Fine Step
- 15 Do You Need Machine Learning
- 16 The Production Problem
- 17 When to Stop
- 18 Stay Up to Date
- 19 Team Sport
- 20 Ethical ML
- 21 Example
- 22 Ethical AI
- 23 Responsible AI
- 24 Data Centric
- 25 Good Data Set
- 26 DataCentric Approach
- 27 Model Diagnostic
- 28 Active Learning
- 29 Improvement
- 30 Infrastructure
- 31 Enemies
- 32 Infrastructure Match Readiness
- 33 Development Production Tension
- 34 Recap
- 35 Resources
