Introduction to Statistical and Machine Learning Methods for Data Science
This book provides a comprehensive overview of the statistical and machine learning techniques associated with data science initiatives. You will learn the most important techniques and methods related to data science and when to apply them for different business problems.
JMP® for Mixed Models
JMP® for Mixed Models is a comprehensive introduction to and reference manual on the use of mixed models with JMP software. The topics covered are analysis of simple, intermediate and complex experiments using mixed model methods in JMP, specifically DOE, single and multiple random effect models, repeated measures and spatial models, random coefficient models, and power analysis. Mixed models are essential for researchers and data analysts, and JMP is the ideal visual and intuitive tool, with a unique approach to graphical statistics.
Segmentation Analytics Using SAS® Viya®: A Practical Approach to Clustering and Visualization for Segmentation
By Randall S. Collica
Anticipated publication date: Second quarter 2021
Segmentation Analytics Using SAS® Viya®: A Practical Approach to Clustering and Visualization for Segmentation demonstrates the use of clustering and ML methods for the purpose of segmenting customer or client data into useful categories for marketing, market research, next best offers by segment, etc. This book will highlight the latest and greatest methods available that show the power of SAS Viya while also solving typical industry issues. This book will provide readers with practical methods of using SAS VDMML Model Studio and coding in SAS Studio for segmentation model development, monitoring, and profiling of segments. Understanding how customers behave is a primary objective of most organizations, and segmentation is a key analytic method for achieving that objective.