A Beginner's Guide to Machine Learning Algorithms
"A Beginner's Guide to Machine Learning Algorithms" is an accessible and comprehensive introduction to the fascinating world of machine learning. This book is designed to demystify complex concepts and provide readers with a solid foundation in the principles and applications of machine learning algorithms.
The book begins by explaining the core concepts of machine learning, including data types, training processes, and the importance of data quality. It breaks down complex topics into digestible sections, ensuring clarity for beginners.
Readers will explore various machine learning paradigms, including supervised, unsupervised, semi-supervised, and reinforcement learning. Each type is explained with real-world examples to illustrate their practical applications.
Whether you're aiming to enhance your career prospects or simply satisfy your curiosity about AI and data science, this book provides the knowledge and tools to understand and implement machine learning algorithms with confidence.
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The book begins by explaining the core concepts of machine learning, including data types, training processes, and the importance of data quality. It breaks down complex topics into digestible sections, ensuring clarity for beginners.
Readers will explore various machine learning paradigms, including supervised, unsupervised, semi-supervised, and reinforcement learning. Each type is explained with real-world examples to illustrate their practical applications.
Whether you're aiming to enhance your career prospects or simply satisfy your curiosity about AI and data science, this book provides the knowledge and tools to understand and implement machine learning algorithms with confidence.
A Beginner's Guide to Machine Learning Algorithms
"A Beginner's Guide to Machine Learning Algorithms" is an accessible and comprehensive introduction to the fascinating world of machine learning. This book is designed to demystify complex concepts and provide readers with a solid foundation in the principles and applications of machine learning algorithms.
The book begins by explaining the core concepts of machine learning, including data types, training processes, and the importance of data quality. It breaks down complex topics into digestible sections, ensuring clarity for beginners.
Readers will explore various machine learning paradigms, including supervised, unsupervised, semi-supervised, and reinforcement learning. Each type is explained with real-world examples to illustrate their practical applications.
Whether you're aiming to enhance your career prospects or simply satisfy your curiosity about AI and data science, this book provides the knowledge and tools to understand and implement machine learning algorithms with confidence.
The book begins by explaining the core concepts of machine learning, including data types, training processes, and the importance of data quality. It breaks down complex topics into digestible sections, ensuring clarity for beginners.
Readers will explore various machine learning paradigms, including supervised, unsupervised, semi-supervised, and reinforcement learning. Each type is explained with real-world examples to illustrate their practical applications.
Whether you're aiming to enhance your career prospects or simply satisfy your curiosity about AI and data science, this book provides the knowledge and tools to understand and implement machine learning algorithms with confidence.
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A Beginner's Guide to Machine Learning Algorithms
A Beginner's Guide to Machine Learning Algorithms
eBook
$9.99
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9.99
In Stock
Product Details
| BN ID: | 2940184629896 |
|---|---|
| Publisher: | Anandakumar Kumaravelu |
| Publication date: | 11/17/2024 |
| Sold by: | Barnes & Noble |
| Format: | eBook |
| File size: | 1 MB |
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