Mathematical Theories of Machine Learning – Theory and Applications (Hardback or

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Machine learning is a rapidly growing field that has revolutionized many industries, from healthcare to finance to marketing. As machine learning algorithms become more sophisticated and powerful, understanding the underlying mathematical theories becomes essential for practitioners and researchers alike.

In this comprehensive book, we delve into the mathematical theories behind machine learning algorithms and their applications. From linear algebra to calculus to probability theory, we cover the foundational concepts that form the basis of machine learning. We also explore advanced topics such as optimization theory, information theory, and statistical learning theory, providing a deep understanding of how machine learning algorithms work.

Through a combination of theory and practical applications, this book serves as a valuable resource for anyone looking to deepen their understanding of machine learning. Whether you are a student, researcher, or industry professional, this book will equip you with the knowledge and tools needed to tackle complex machine learning problems with confidence.

Available in both hardback and eBook formats, this book is a must-have for anyone interested in the mathematical theories of machine learning. Order your copy today and take your machine learning skills to the next level!
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