Description
This authoritative handbook provides an in-depth exploration of contemporary computer learning and intelligence methodologies. It covers essential topics including explainable AI (XAI), which addresses the critical need for transparency in machine learning models, alongside comprehensive coverage of supervised learning approaches.
The book delves into deep learning architectures and their applications, offering practical insights into neural networks and advanced computational models. Additionally, it examines intelligent control systems and their implementation in real-world scenarios. The evolutionary computation section explores algorithms inspired by natural selection and their role in solving complex optimization problems.
Written by renowned expert Plamen Parvanov Angelov, this resource serves as both a theoretical foundation and practical guide for professionals, researchers, and students seeking to understand modern AI systems, interpretability, and advanced machine learning techniques.
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