Foundations of Machine Learning: A Practical Guide to Concepts, Tools, and Applications

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Bol Welcome to "Foundations of Machine Learning: A Practical Guide to Concepts, Tools, and Applications", a comprehensive introduction to the exciting world of machine learning. This book is designed for beginners and enthusiasts who are curious about understanding the core principles of machine learning and its applications in the real world.Machine learning, a cornerstone of modern artificial intelligence, has revolutionized industries by enabling systems to learn from data and improve over time. From healthcare and finance to entertainment and transportation, machine learning is driving innovation across diverse fields. This book serves as your gateway to mastering foundational concepts and acquiring the skills needed to dive deeper into this transformative domain.Throughout this guide, we explore key topics such as the paradigms of machine learning, mathematical foundations, data-driven approaches, and the implementation of popular algorithms. You will also gain insights into essential tools like linear algebra, regression techniques, and advanced models such as support vector machines and ensemble methods.

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Welcome to "Foundations of Machine Learning: A Practical Guide to Concepts, Tools, and Applications", a comprehensive introduction to the exciting world of machine learning. This book is designed for beginners and enthusiasts who are curious about understanding the core principles of machine learning and its applications in the real world.Machine learning, a cornerstone of modern artificial intelligence, has revolutionized industries by enabling systems to learn from data and improve over time. From healthcare and finance to entertainment and transportation, machine learning is driving innovation across diverse fields. This book serves as your gateway to mastering foundational concepts and acquiring the skills needed to dive deeper into this transformative domain.Throughout this guide, we explore key topics such as the paradigms of machine learning, mathematical foundations, data-driven approaches, and the implementation of popular algorithms. You will also gain insights into essential tools like linear algebra, regression techniques, and advanced models such as support vector machines and ensemble methods.

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Pages: 148, Paperback, LAP Lambert Academic Publishing


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Merk LAP LAMBERT Academic Publishing
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  • 9786209933615
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