By Jonathan Davis Published by ScaledLearning Available now

Data Quality for AI

Clean, complete and contextual data for models and agents

Garbage in, garbage out, now at machine speed. Practical methods for measuring and improving data quality so that models, LLMs and agents can be trusted.

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What you'll learn

• Measure data quality continuously
• Fix data problems at the source
• Improve the context that LLMs and agents retrieve

Contents

1. Chapter 1 The cost of bad data in AI
2. Chapter 2 Dimensions of data quality
3. Chapter 3 Measuring quality continuously
4. Chapter 4 Fixing data at the source
5. Chapter 5 Quality for LLM context and retrieval
6. Chapter 6 A data quality operating rhythm

By Jonathan Davis · Published by ScaledLearning