A Modern and Scalable Approach to Responsible AI

A Modern and Scalable Approach to Responsible AI

Audit, Assess, and Evaluate AI Systems

Understanding machine learning (ML) systems is a critical task for data scientists and non-technical profiles alike as organizations aim to integrate AI applications on an enterprise-wide level.

In this ebook, we take a look at the relationship between these profiles and practices to identify cutting-edge and responsible strategies for managing high-impact AI systems.

Early Release Chapters 1-3 Feature:

  • A precis of all of that model governance encompasses today and the best execution methods for practitioners
  • Insight into the best practices for debugging ML systems for safety and performance
  • An overview of data and security for ML to effectively audit for any potential vulnerabilities

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