Learn Data Mining Through Excel: A Step-By-Step Approach for Understanding Machine Learning Methods 2/e

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.

使用流行的資料探勘技術在Microsoft Excel中，以更好地理解機器學習方法。大多數軟體工具和程式語言套件接收資料輸入並直接提供資料探勘結果，但卻無法提供工作機制的洞察力，造成輸入和輸出之間的鴻溝。這就是Excel的用武之地，而本書將向您展示如何做到這一點。

這本更新的版本演示了如何透明地使用Excel處理資料。當您打開一個Excel檔案時，資料立即可見，您可以直接使用它。您將看到如何在進行資料探勘任務的同時檢查中間結果，從而更深入地了解資料是如何被操作和獲取結果的。這些是模型構建過程中常常隱藏在軟體工具和程式語言套件中的關鍵方面。

在《透過Excel學習資料探勘》的過程中，您將學習到當資料集不太大時，這個應用程式提供的資料探勘優勢。您將看到如何使用Excel內建的功能來創建資料的視覺化表示，使您能夠以易於理解的格式呈現您的發現。作者Hong Zhou將引導您完成每一個步驟，不僅提供積極的學習體驗，還教您資料探勘過程的運作方式以及如何在資料中找到隱藏的模式。

完成本書後，您將全面了解如何使用您可能已經擁有的應用程式來進行資料探勘和分析，以及如何以各種格式呈現結果。

您將學到什麼：
- 以視覺化的逐步方法理解資料探勘
- 瞭解資料探勘的基礎知識
- 在Excel中實施資料探勘方法
- 理解機器學習演算法
- 創造性地利用Excel公式和函數
- 獲得資料探勘和Excel的實踐經驗

適合對學習資料探勘或機器學習感興趣的任何人，尤其是對資料科學有視覺化學習需求和熟練使用Excel的人，他們希望探索資料科學主題和/或擴展Excel技能。建議具備基本或初級水平的Excel理解能力。

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 nearly 20 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.

Hong Zhou博士是一位計算機科學和數學教授，並在聖約瑟夫大學教授計算機科學、數據科學、數學和信息學課程近20年。他的研究興趣包括生物信息學、數據挖掘、軟件代理和區塊鏈。在目前的職位之前，他曾在矽谷擔任Java開發人員。周博士認為，學習者在視覺上逐步體驗數據挖掘模型時，可以建立更好的基礎，而這正是Excel所提供的。他在教授數據挖掘時使用Excel，並發現這對於數據挖掘學習者和教育工作者都是一種有效的方法。