A Guide to AI Explainability
This ebook presents an overview of the latest techniques for achieving explainability, equipping you with the skills to build trustworthy AI models.
Machine learning and algorithms have become ubiquitous in various fields, but their operations and reasoning are often concealed in a black box, creating uncertainty. AI Explainability refers to the process of uncovering the reasons behind a model's decisions. This ebook emphasizes the importance of Explainability in AI systems and provides a range of tools and techniques to integrate Explainability into your processes. The ebook covers the following topics:
- The significance of Explainability in AI systems
- Understanding the basics of Explainability
- Techniques for building Explainable AI models
- Tools for incorporating Explainability into AI systems
- Best practices for achieving Explainability in AI systems.