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{ "item_title" : "Applied Machine Learning - From Cyber Security to Medical Diagnosis", "item_author" : [" Zam Ab "], "item_description" : "This book is designed as a practical and application-oriented introduction to machine learning, with a strong focus on real-world domains such as financial fraud detection, medical diagnosis, and customer analytics. Rather than presenting machine learning only through theory, the book emphasizes hands-on learning, real datasets, and practical scenarios that allow readers to understand how machine learning techniques are implemented in real environments.The chapters are structured in a progressive manner so that readers can move from foundational concepts to more advanced applications and practical implementations. Each chapter combines conceptual explanations, diagrams, case studies, and Python-based exercises so that readers can develop both theoretical understanding and practical skills.The book currently consists of nine chapters, each designed to address a specific aspect of machine learning and its applications.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/825/393/9798253936283_b.jpg", "price_data" : { "retail_price" : "33.50", "online_price" : "33.50", "our_price" : "33.50", "club_price" : "33.50", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Applied Machine Learning - From Cyber Security to Medical Diagnosis|Zam Ab

Applied Machine Learning - From Cyber Security to Medical Diagnosis

by Zam Ab
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Overview

This book is designed as a practical and application-oriented introduction to machine learning, with a strong focus on real-world domains such as financial fraud detection, medical diagnosis, and customer analytics. Rather than presenting machine learning only through theory, the book emphasizes hands-on learning, real datasets, and practical scenarios that allow readers to understand how machine learning techniques are implemented in real environments.
The chapters are structured in a progressive manner so that readers can move from foundational concepts to more advanced applications and practical implementations. Each chapter combines conceptual explanations, diagrams, case studies, and Python-based exercises so that readers can develop both theoretical understanding and practical skills.
The book currently consists of nine chapters, each designed to address a specific aspect of machine learning and its applications.

This item is Non-Returnable

Details

  • ISBN-13: 9798253936283
  • ISBN-10: 9798253936283
  • Publisher: Independently Published
  • Publish Date: March 2026
  • Dimensions: 9 x 6 x 0.87 inches
  • Shipping Weight: 1.15 pounds
  • Page Count: 390

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