Learn Data Mining Through Excel

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

Hong Zhou

• Publisher: Apress
• Year: 2023
• ISBN:
  9781484297711
• Edition: 2
• Topic: Informatik
• Subtopic: Microsoft-Programmierung

Use popular data mining techniques in Microsoft Excel to better understand machine learning methods. Most 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, and this book will show you exactly how.

This updated edition demonstrates how to work with data in a transparent manner using Excel. When you open an Excel file, data is visible immediately and you can work with it directly. You'll see how to examine intermediate results even as you are still 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 often hidden in software tools and programming language packages.

Over the course of Learn Data Mining Through Excel, you will learn the data mining advantages the application offers when the data sets are not too large. You'll see how to use Excel's built-in features to create visual representations of your data, enabling you to present your findings in an accessible format. Author Hong Zhou walks you through each step, offering not only an active learning experience, but teaching you how the mining process works and how to find hidden patterns within the data.

Upon completing this book, you will have a thorough understanding of how to use an application you very likely already have to mine and analyze data, and how to present results in various formats.

What You Will Learn

• Comprehend data mining using a visual step-by-step approach
• Gain an introduction to the fundamentals of data mining
• Implement data mining methods in Excel
• Understand machine learning algorithms
• Leverage Excel formulas and functions creatively
• 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.

Table of contents

• Cover
• Front Matter
• 1. Excel and Data Mining
• 2. Linear Regression
• 3. K-Means Clustering
• 4. Linear Discriminant Analysis
• 5. Cross-Validation and ROC
• 6. Logistic Regression
• 7. K-Nearest Neighbors
• 8. Hierarchical Clustering and Dendrogram
• 9. Naive Bayes Classification
• 10. Decision Trees
• 11. EDA, Data Cleaning, and Feature Selection
• 12. Association Analysis
• 13. Artificial Neural Network
• 14. Text Mining
• 15. After Excel
• Back Matter