Applied Analytics Through Case Studies Using Sas And R

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Applied Analytics through Case Studies Using SAS and R

Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms. Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills. What You'll Learn Understand analytics and basic data concepts Use an analytical approach to solve Industrial business problems Build predictive model with machine learning techniques Create and apply analytical strategies Who This Book Is For Data scientists, developers, statisticians, engineers, and research students with a great theoretical understanding of data and statistics who would like to enhance their skills by getting practical exposure in data modeling.
Supply Chain Analytics and Modelling

Author: Nicoleta Tipi
language: en
Publisher: Kogan Page Publishers
Release Date: 2021-04-03
An incredible volume of data is generated at a very high speed within the supply chain and it is necessary to understand, use and effectively apply the knowledge learned from analyzing data using intelligent business models. However, practitioners and students in the field of supply chain management face a number of challenges when dealing with business models and mathematical modelling. Supply Chain Analytics and Modelling presents a range of business analytics models used within the supply chain to help readers develop knowledge on a variety of topics to overcome common issues. Supply Chain Analytics and Modelling covers areas including supply chain planning, single and multi-objective optimization, demand forecasting, product allocations, end-to-end supply chain simulation, vehicle routing and scheduling models. Learning is supported by case studies of specialist software packages for each example. Readers will also be provided with a critical view on how supply chain management performance measurement systems have been developed and supported by reliable and accurate data available in the supply chain. Online resources including lecturer slides are available.
Proceedings on 18th International Conference on Industrial Systems – IS’20

This book proposes theoretically developed and practically tested solutions for manufacturing and business improvements achieved in the period between two conferences. It enables presentation of new knowledge and exchange of practical experience in industrial systems engineering and management. It brings together prominent researchers and practitioners from faculties, scientific institutes, and different enterprises or other organizations .This is the 18th edition of the conference. The Department of Industrial Engineering and Management at the Faculty of Technical Sciences in Novi Sad organizes a scientific conference on industrial systems engineering and management field of science and practice, once in three years.