Learn data mining through excel: a step by step approach for understanding machine learning methods

By:

Zhou, Hong

Material type: Text

TextPublication details: Apress USA 2021Description: xvi, 219 pISBN:

9781484267356

Subject(s):

DDC classification:

004.165 ZHO

Summary: About this book 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 Who 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.

List(s) this item appears in: IT & Decision Sciences | HR & OB

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	IT & Decisions Sciences	004.165 ZHO (Browse shelf(Opens below))	1	Available		003907

Excel and Data Mining
Hong Zhou
Pages 1-19
Linear Regression
Hong Zhou
Pages 21-34
K-Means Clustering
Hong Zhou
Pages 35-47
Linear Discriminant Analysis
Hong Zhou
Pages 49-66
Cross-Validation and ROC
Hong Zhou
Pages 67-81
Logistic Regression
Hong Zhou
Pages 83-92
K-Nearest Neighbors
Hong Zhou
Pages 93-108
Naïve Bayes Classification
Hong Zhou
Pages 109-123
Decision Trees
Hong Zhou
Pages 125-148
Association Analysis
Hong Zhou
Pages 149-161
Artificial Neural Network
Hong Zhou
Pages 163-187
Text Mining
Hong Zhou
Pages 189-209
After Excel

About this book
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

Who 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.

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