This book explores the growing focus on artificial intelligence (AI) systems in both industry and academia. It evaluates and justifies AI applications while enhancing trust in AI outcomes and aiding comprehension of AI feature development. Key topics include an overview of explainable AI, black box model understanding, interpretability techniques, practical XAI applications, and future trends and challenges in XAI.

Technical topics discussed in the book include:

• Explainable AI overview
• Understanding black box models
• Techniques for model interpretability
• Practical applications of XAI
• Future trends and challenges in XAI

This book explores the growing focus on artificial intelligence (AI) systems in both industry and academia. It evaluates and justifies AI applications while enhancing trust in AI outcomes and aiding comprehension of AI feature development. Key topics include an overview of explainable AI, black box model understanding, interpretability techniques, practical XAI applications, and future trends and challenges in XAI.

Technical topics discussed in the book include:

• Explainable AI overview
• Understanding black box models
• Techniques for model interpretability
• Practical applications of XAI
• Future trends and challenges in XAI

This book explores the growing focus on artificial intelligence (AI) systems in both industry and academia. It evaluates and justifies AI applications while enhancing trust in AI outcomes and aiding comprehension of AI feature development. Key topics include an overview of explainable AI, black box model understanding, interpretability techniques, practical XAI applications, and future trends and challenges in XAI.

Technical topics discussed in the book include:

• Explainable AI overview
• Understanding black box models
• Techniques for model interpretability
• Practical applications of XAI
• Future trends and challenges in XAI