Machine Learning for Business Analytics 1st Edition

Machine Learning for Business Analytics (1st Edition) by Hemachandran K. is a practical, classroom-ready guide that bridges rigorous machine learning concepts with real-world business decision-making. Clear, concise and designed for busy professionals, this book transforms complex algorithms into actionable strategies for marketing, finance, operations and supply chain teams.

You’ll find an engaging introduction to core topics—supervised and unsupervised learning, feature engineering, model selection, evaluation metrics, and deployment considerations—explained through business-focused examples. Each chapter emphasizes interpretation, ROI-driven model choice, and how to translate predictive insights into measurable business outcomes, making it ideal for data analysts, managers, MBA students, and executives seeking competitive advantage.

What sets this first edition apart is its balance of theory and application: practical case studies, step-by-step workflows for building and validating models, and templates for presenting results to stakeholders. Whether you’re developing customer segmentation, demand forecasting, churn prediction, or pricing optimization, the book gives you the tools to implement data-driven solutions that work across markets—from India and Southeast Asia to Europe and the Americas.

Readable yet authoritative, Hemachandran K.’s approach equips readers to move beyond tools to strategic thinking—turning models into decisions that improve performance. Pick up this essential resource to sharpen your analytics practice and drive measurable business impact. Order your copy today and start applying machine learning techniques tailored for real-world business challenges.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.