Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver Data Mining van Galit Shmueli, Peter C. Bruce, Kuber R. Deokar is een Engelstalig gedrukt boek. Deze titel is geschikt voor professionals.
MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning-also known as data mining or predictive analytics-is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver (R) Data Mining provides a comprehensive introduction and an overview of this methodology. The fourth edition of this best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, time series forecasting 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. This fourth edition of Machine Learning for Business Analytics also includes: An expanded chapter on deep learning; A new chapter on experimental feedback techniques, including A/B testing, uplift modeling, and reinforcement learning; A new chapter on responsible data science; Updates 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; A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques; End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented; A companion website with more than two dozen data sets, and instructor m
Inhoudelijk sluit dit boek aan bij onderwerpen als Electronics and communications engineering, Data mining, TECHNOLOGY & ENGINEERING / Electronics / General.