{"product_id":"understanding-machine-learning-concepts-supervised-vs-unsupervised-learning-in-r-9798269533926","title":"Understanding Machine Learning Concepts: Supervised vs. Unsupervised Learning in R","description":"\u003cp\u003e • Author(s): Felix A. Okolie | Joseph Solomon | Dorcas O. Folarin\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Probability \u0026amp; Statistics - General\u003c\/p\u003e\u003cp\u003e\u003cb\u003eUnderstanding Machine Learning Concepts: Supervised vs. Unsupervised Learning in R\u003c\/b\u003e is a practical, comprehensive guide that bridges theory and application for learners, researchers, and professionals in data science.\u003cbr\u003eWritten in clear, accessible language, this book demystifies the principles of machine learning through hands-on R implementations and real-world examples.\u003cbr\u003eBeginning with foundational concepts and data preprocessing, readers progress through supervised learning techniques such as regression and classification, before diving into unsupervised methods including clustering, dimensionality reduction, and association rule mining. Each chapter provides practical R code snippets, visualizations, and exercises that make complex topics intuitive and applicable.\u003cbr\u003eFrom evaluating model performance to understanding when and why to use supervised or unsupervised approaches, this book equips readers with the knowledge and confidence to build, validate, and interpret machine learning models effectively.\u003cbr\u003eWhether you are a \u003cb\u003estudent exploring data analytics\u003c\/b\u003e, a \u003cb\u003eresearcher applying predictive models\u003c\/b\u003e, or a \u003cb\u003eprofessional seeking to expand your R programming skills\u003c\/b\u003e, this book serves as a complete roadmap to mastering machine learning fundamentals.\u003cbr\u003e\u003cb\u003eHighlights: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eA clear comparison between supervised and unsupervised learning paradigms.\u003c\/li\u003e\n\u003cli\u003eStep-by-step R examples for regression, classification, clustering, and dimensionality reduction.\u003c\/li\u003e\n\u003cli\u003eIn-depth discussions on data preprocessing, feature engineering, and model validation.\u003c\/li\u003e\n\u003cli\u003eReal-world case studies demonstrating end-to-end R applications.\u003c\/li\u003e\n\u003cli\u003eA glossary of key machine learning and R terms for quick reference.\u003c\/li\u003e\n\u003cli\u003eForward-looking insights into automation, interpretability, and ethical AI in R.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Atlantic Books","offers":[{"title":"Paperback","offer_id":46332058828951,"sku":"9798269533926","price":1779.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798269533926.webp?v=1768725080","url":"https:\/\/atlanticbooks.com\/products\/understanding-machine-learning-concepts-supervised-vs-unsupervised-learning-in-r-9798269533926","provider":"Atlantic Books","version":"1.0","type":"link"}