Description
Machine Learning for Business Applications is a practical guide that bridges the gap between theoretical machine learning concepts and real-world business implementation. Written by Pratyush Banerjee, Supriti Mishra, and Shivashankar Chari, this book focuses on concrete case studies and practical applications rather than complex mathematics.
The book covers essential machine learning algorithms tailored for business contexts, including supervised learning, unsupervised learning, and predictive modeling techniques. Each concept is illustrated through detailed business case studies that demonstrate how organizations successfully implement ML solutions across various industries.
Ideal for business professionals, managers, and aspiring data scientists, this McGraw Hill publication provides actionable insights into leveraging machine learning for competitive advantage. Readers will gain practical knowledge applicable to customer segmentation, demand forecasting, fraud detection, and process optimization.
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