{"title":"Inbal Yahav","description":"\u003cp\u003eInbal Yahav is a distinguished author and academic whose work bridges the intricate worlds of machine learning and business analytics. Her books appeal to readers who are keen to explore the interplay between data science, artificial intelligence, and business decision-making.\u003c\/p\u003e\n\n\u003cp\u003eOne of her notable works, \u003cem\u003eMachine Learning for Business Analytics\u003c\/em\u003e, delves into the practical applications of machine learning techniques in the business environment. It provides comprehensive insights into how machine learning can transform data into actionable strategies, making it an invaluable resource for both students and professionals in the field.\u003c\/p\u003e\n\n\u003cp\u003eInbal's writing is celebrated for its clarity and accessibility, making complex scientific concepts understandable and applicable to real-world business challenges. Her contributions to the \u003cstrong\u003eScience \u0026amp; Nature\u003c\/strong\u003e category have made significant impacts, offering readers not only theoretical understanding but also practical tools to implement in various business contexts.\u003c\/p\u003e\n\n\u003cp\u003eWhether you're a seasoned professional or a curious learner, Inbal Yahav's work is sure to enrich your understanding of how machine learning can be harnessed to drive business success.\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\/inbal-yahav.oembed","provider":"Book Hero","version":"1.0","type":"link"}