Description
Machine Learning Algorithms and Applications in Engineering provides engineers and professionals with a thorough exploration of machine learning techniques and their implementation in engineering contexts. The book bridges the gap between theoretical concepts and practical applications, offering insights into how intelligent computing systems can solve complex engineering problems.
Written by leading experts including Prasenjit Chatterjee and Morteza Yazdani, this volume covers fundamental algorithms, advanced methodologies, and case studies demonstrating real-world applications. Topics include supervised learning, unsupervised learning, neural networks, optimization algorithms, and deep learning frameworks. The work emphasizes smart and intelligent computing approaches relevant to modern engineering challenges.
Ideal for engineers, researchers, and students, this resource serves as both a learning tool and reference guide for implementing machine learning solutions in industrial and academic settings.
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