隨著網際網路以及資料庫技術的發達，人們搜尋資料變得愈來愈容易，透過網路我們可以輕易地獲取大量的資料，於是在資料充斥的情況之下，現代的資訊技術所要面臨的挑戰已經不是如何管理資料，而是如何從這些大量的資料當中，找出真正有用的資訊，而要滿足這個需求最主要的方法就是仰賴資料探勘的技術。資料探勘是一個利用各種分析工具在大量資料中發現模型和資料間關係的過程，使用這些模型和關係可以進行預測，它幫助決策者尋找資料間潛在的關聯，發現被忽略的因素，因而認為是解當今時代所面臨的資料爆炸而資訊貧乏問題的一種有效方法。
With the development of the Internet and database technology, it has become easier and easier for people to search for information. We can easily obtain a large amount of information through the Internet. Therefore, in a situation where data is abundant, modern information technology has to face The challenge is no longer how to manage data, but how to find truly useful information from these large amounts of data. The main way to meet this demand is to rely on data mining technology. Data mining is a process that uses various analysis tools to discover models and relationships between data in a large amount of data. These models and relationships can be used to make predictions. It helps decision-makers find potential correlations between data and discover overlooked factors. Therefore, it is considered An effective way to solve the problem of data explosion and lack of information faced in today's era.
讓學生知悉資料探勘如何運作，原理為何
Let students know how data mining works and what its principles are.
1.資料探勘 (旗標)
2.資料探勘原理與技術 (五南)
3.資料探勘─人工智慧與機器學習發展-以 SPSS Modeler為範例 (博碩文化)
4.資料探勘 (滄海)
5.資料探勘 (PEARSON, 歐亞書局代理)
1. Data exploration (flag)
2. Data exploration principles and techniques (Wunan)
3. Data exploration─The development of artificial intelligence and machine learning-taking SPSS Modeler as an example (Ph.D. culture)
4. Data exploration (Canghai)
5. Data exploration (PEARSON, agent of Eurasian Book Company)
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 平時成績(出席、參與及作業)平時成績(出席、參與及作業) Daily results (attendance, participation and homework) |
30 | 作業(20%) |
| 期中考期中考 midterm exam |
25 | |
| 分組報告分組報告 Group report |
20 | |
| 期末報告期末報告 Final report |
25 |
