We have reviewed some basic decision systems by taking two samples, that is, Bayesian and fuzzy logic. We also explored Python libraries for implementing Bayesian and fuzzy logic and then practiced with them. As the last topic, we deployed a decision system using fuzzy logic as a study sample on how to integrate a decision system on an IoT project with Raspberry Pi.

Advanced Analytics with R and Tableau
By :

Advanced Analytics with R and Tableau
By:
Overview of this book
Tableau and R offer accessible analytics by allowing a combination of easy-to-use data visualization along with industry-standard, robust statistical computation.
Moving from data visualization into deeper, more advanced analytics? This book will intensify data skills for data viz-savvy users who want to move into analytics and data science in order to enhance their businesses by harnessing the analytical power of R and the stunning visualization capabilities of Tableau. Readers will come across a wide range of machine learning algorithms and learn how descriptive, prescriptive, predictive, and visually appealing analytical solutions can be designed with R and Tableau. In order to maximize learning, hands-on examples will ease the transition from being a data-savvy user to a data analyst using sound statistical tools to perform advanced analytics.
By the end of this book, you will get to grips with advanced calculations in R and Tableau for analytics and prediction with the help of use cases and hands-on examples.
Table of Contents (16 chapters)
Advanced Analytics with R and Tableau
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Advanced Analytics with R and Tableau
The Power of R
A Methodology for Advanced Analytics Using Tableau and R
Prediction with R and Tableau Using Regression
Classifying Data with Tableau
Advanced Analytics Using Clustering
Advanced Analytics with Unsupervised Learning
Interpreting Your Results for Your Audience
Index
Customer Reviews