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.
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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.