Explainable AI: Building Trustworthy Deep Learning Systems (Prospects in Smart Technologies)

With the increasing use of deep learning systems across various industries, there is a growing need to make their decision-making processes more understandable and transparent.Regulatory requirements now demand clarity, and users and stakeholders want to know how AI systems work.The textbook addresses these needs by providing a detailed guide on integrating Explainable AI (XAI) into the Deep Learning Operations (DLOps) pipeline.By doing so, organizations can implement Continuous Integration (CI) and Continuous Deployment (CD) practices effectively. Explainable AI: Building Trustworthy Deep Learning Systems focuses on how to incorporate XAI models, tools, and techniques to clarify machine learning decisions.It explores applications in fields such as healthcare, defense, human activity recognition, and object identification.The book offers practical advice on embedding XAI tools throughout the lifecycle of deep learning systems, covering topics like Explainability and Interpretability, D