{"title":"Peter Gedeck","description":"\u003cp\u003eDiscover the innovative world of data science and analytics with the works of \u003cem\u003ePeter Gedeck\u003c\/em\u003e, a renowned author in the field of machine learning and its practical applications. Peter Gedeck has crafted insightful books that bridge the gap between complex scientific concepts and real-world business solutions, making them accessible to both novices and seasoned professionals.\u003c\/p\u003e\n\n\u003cp\u003eOne of the standout books in this collection is \u003cstrong\u003eMachine Learning for Business Analytics\u003c\/strong\u003e. This comprehensive guide provides a detailed exploration of how data-driven strategies can transform business operations, equipping readers with the tools needed to harness the power of machine learning for enhanced decision-making and competitive advantage.\u003c\/p\u003e\n\n\u003cp\u003ePerfectly categorised under \u003cem\u003eScience \u0026amp; Nature\u003c\/em\u003e, Gedeck’s books extend beyond mere theory, offering practical insights tailored to modern business environments. Readers will gain an understanding of the latest techniques in data analysis and how these can be effectively implemented in various industries.\u003c\/p\u003e\n\n\u003cp\u003eIf you are curious about the ever-evolving landscape of machine learning and its impact on contemporary business practices, Peter Gedeck’s works are an essential addition to your library, offering a blend of educational content and actionable strategies.\u003c\/p\u003e","products":[{"product_id":"machine-learning-for-business-analytics-by-inbal-yahav-9781119835172","title":"Machine Learning for Business Analytics","description":"\u003cdiv class=\"book-description\"\u003e\n\u003cp\u003e\u003cem\u003eMachine Learning for Business Analytics\u003c\/em\u003e\u003c\/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eMachine learning\u003c\/strong\u003e—also known as data mining or data analytics—is a fundamental part of data science. It is used by organisations in a wide variety of arenas to turn raw data into actionable information.\u003c\/p\u003e\n\n\u003cp\u003e\u003cem\u003eMachine Learning for Business Analytics: Concepts, Techniques, and Applications in R\u003c\/em\u003e provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualisation, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques.\u003c\/p\u003e\n\n\u003cp\u003eThis is the second R edition of \u003cem\u003eMachine Learning for Business Analytics\u003c\/em\u003e. This edition also includes:\u003c\/p\u003e\n\n\u003cul\u003e\n  \u003cli\u003eA new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using R.\u003c\/li\u003e\n  \u003cli\u003eAn expanded chapter focused on the discussion of deep learning techniques.\u003c\/li\u003e\n  \u003cli\u003eA new chapter on experimental feedback techniques including A\/B testing, uplift modelling, and reinforcement learning.\u003c\/li\u003e\n  \u003cli\u003eA new chapter on responsible data science.\u003c\/li\u003e\n  \u003cli\u003eUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma, and executive courses, and from their students.\u003c\/li\u003e\n  \u003cli\u003eA full chapter devoted to relevant case studies, with more than a dozen cases demonstrating applications for the machine learning techniques.\u003c\/li\u003e\n  \u003cli\u003eEnd-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented.\u003c\/li\u003e\n  \u003cli\u003eA companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003eThis textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Unknown","offers":[{"title":"Default Title","offer_id":46854647841004,"sku":"9781119835172","price":274.99,"currency_code":"NZD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0705\/7784\/8556\/files\/9781119835172.jpg?v=1759250878"}],"url":"https:\/\/bookhero.pro\/collections\/peter-gedeck.oembed","provider":"Book Hero","version":"1.0","type":"link"}