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Covers diverse applications of machine learning models for real-world problem-solving
Discusses conceptualization, data representation, and feature engineering in detail
Provides critical comparisons with existing techniques for informed decision-making
Explores methodologies and interpretations behind the presented results
Hardcover format for durability and professional presentation
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This reprint focuses on applications of machine learning models in a diverse range of fields and problems. It reports substantive results on a wide range of learning methods; discusses the conceptualization of problems, data representation, feature engineering, and machine learn
