Data Mining and Predictive Analytics for Business Decisions: A Case Study Approach eBook

Delivery: Can be download immediately after purchasing. For new customer, we need process for verification from 30 mins to 12 hours.
Version: PDF/EPUB. If you need EPUB and MOBI Version, please send contact us.
Compatible Devices: Can be read on any devices

With many recent advances in data science, we have many more tools and techniques available for data analysts to extract information from data sets. This book will assist data analysts to move up from simple tools such as Excel for descriptive analytics to answer more sophisticated questions using machine learning. Most of the exercises use R and Python, but rather than focus on coding algorithms, the book employs interactive interfaces to these tools to perform the analysis. Using the CRISP-DM data mining standard, the early chapters cover conducting the preparatory steps in data mining: translating business information needs into framed analytical questions and data preparation. The Jamovi and the JASP interfaces are used with R and the Orange3 data mining interface with Python. Where appropriate, Voyant and other open-source programs are used for text analytics. The techniques covered in this book range from basic descriptive statistics, such as summarization and tabulation, to more sophisticated predictive techniques, such as linear and logistic regression, clustering, classification, and text analytics. Includes companion files with case study files, solution spreadsheets, data sets and charts, etc. from the book.

FEATURES:
Covers basic descriptive statistics, such as summarization and tabulation, to more sophisticated predictive techniques, such as linear and logistic regression, clustering, classification, and text analytics
Uses R, Python, Jamovi and JASP interfaces, and the Orange3 data mining interface
Includes companion files with the case study files from the book, solution spreadsheets, data sets, etc.

This is a digital product.

Data Mining and Predictive Analytics for Business Decisions: A Case Study Approach is written by Andres Fortino and published by Mercury Learning & Information. The Digital and eTextbook ISBNs for Data Mining and Predictive Analytics for Business Decisions: A Case Study Approach are 9781683926733, 1683926730 and the print ISBNs are 9781683926757, 1683926757.