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© 2020

Learn Data Mining Through Excel

A Step-by-Step Approach for Understanding Machine Learning Methods

Book

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Hong Zhou
    Pages 1-19
  3. Hong Zhou
    Pages 21-34
  4. Hong Zhou
    Pages 35-47
  5. Hong Zhou
    Pages 49-66
  6. Hong Zhou
    Pages 67-81
  7. Hong Zhou
    Pages 83-92
  8. Hong Zhou
    Pages 93-108
  9. Hong Zhou
    Pages 109-123
  10. Hong Zhou
    Pages 125-148
  11. Hong Zhou
    Pages 149-161
  12. Hong Zhou
    Pages 163-187
  13. Hong Zhou
    Pages 189-209
  14. Hong Zhou
    Pages 211-213
  15. Back Matter
    Pages 215-219

About this book

Introduction

Use popular data mining techniques in Microsoft Excel to better understand machine learning methods.

Software tools and programming language packages take data input and deliver data mining results directly, presenting no insight on working mechanics and creating a chasm between input and output. This is where Excel can help.

Excel allows you to work with data in a transparent manner. When you open an Excel file, data is visible immediately and you can work with it directly. Intermediate results can be examined while you are conducting your mining task, offering a deeper understanding of how data is manipulated and results are obtained. These are critical aspects of the model construction process that are hidden in software tools and programming language packages.

This book teaches you data mining through Excel. You will learn how Excel has an advantage in data mining when the data sets are not too large. It can give you a visual representation of data mining, building confidence in your results. You will go through every step manually, which offers not only an active learning experience, but teaches you how the mining process works and how to find the internal hidden patterns inside the data. 

What You Will Learn:

  • Comprehend data mining using a visual step-by-step approach
  • Build on a theoretical introduction of a data mining method, followed by an Excel implementation
  • Unveil the mystery behind machine learning algorithms, making a complex topic accessible to everyone
  • Become skilled in creative uses of Excel formulas and functions
  • Obtain hands-on experience with data mining and Excel
This book is for anyone who is interested in learning data mining or machine learning, especially data science visual learners and people skilled in Excel, who would like to explore data science topics and/or expand their Excel skills. A basic or beginner level understanding of Excel is recommended.

Hong Zhou, PhD is a professor of computer science and mathematics and has been teaching courses in computer science, data science, mathematics, and informatics at the University of Saint Joseph for more than 15 years. His research interests include bioinformatics, data mining, software agents, and blockchain. Prior to his current position, he was as a Java developer in Silicon Valley. Dr. Zhou believes that learners can develop a better foundation of data mining models when they visually experience them step-by-step, which is what Excel offers. He has employed Excel in teaching data mining and finds it an effective approach for both data mining learners and educators.

Keywords

Data mining Excel machine learning decision trees clustering data classification linear regresssion data analysis nearest neighbors Naive Bayes k-means clustering cross-validation neural network logistic regression analysis Hong Zhou Excel

Authors and affiliations

  1. 1.University of Saint JosephWest HartfordUSA

About the authors

Hong Zhou, PhD is a professor of computer science and mathematics and has been teaching courses in computer science, data science, mathematics, and informatics at the University of Saint Joseph for more than 15 years. His research interests include bioinformatics, data mining, software agents, and blockchain. Prior to his current position, he was as a Java developer in Silicon Valley. Dr. Zhou believes that learners can develop a better foundation of data mining models when they visually experience them step-by-step, which is what Excel offers. He has employed Excel in teaching data mining and finds it an effective approach for both data mining learners and educators.

Bibliographic information

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