Description
Machine Learning Theory and Applications offers a comprehensive exploration of machine learning concepts paired with practical, hands-on implementations. Written by Xavier Vasques and published by Wiley, this book bridges the gap between theoretical foundations and real-world applications.
The text covers essential ML algorithms, statistical foundations, and modern techniques applicable to classical computing environments. Additionally, it ventures into the emerging field of quantum machine learning, preparing readers for the next generation of computational possibilities.
With practical Python examples throughout, this book serves both beginners seeking foundational knowledge and experienced practitioners exploring quantum computing applications. The hands-on approach ensures readers can immediately apply concepts to their own projects, making it an invaluable resource for data scientists, machine learning engineers, and technology professionals.
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