介紹
This course provides a structured introduction to the theory of data mining. It begins with the foundations, defining what data mining is and examining illustrative applications. Core concepts such as types of attributes, data quality issues, and preprocessing strategies including aggregation, sampling, feature selection, and dimensionality reduction are then introduced. The course proceeds with exploratory data analysis, covering descriptive statistics, frequency distributions, and visualization methods. Students will study supervised learning models, focusing on classification, decision trees, and neural networks, followed by an introduction to natural language processing, language models, and transformers. Finally, the course examines unsupervised learning techniques, including clustering and association rules, as theoretical frameworks for uncovering patterns and relationships within data. By the end, students will gain a comprehensive understanding of the theoretical underpinnings of data mining across both structured and unstructured data.
章節
* 以下章節為預覽，請點報名後點選開始上課，進入課程-
Week 1 : Introduction, Types of Attributes, Data Quality Issues
- ● What is Data Mining, Data Mining Examples
- ● Types of Attributes
- ● Data Problems - Noise, Outlier, duplicated
- ● Exercise 1
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Week 2 : Aggregation and Sampling, Curse of Dimensionality, and Data Shaping
- ● Aggregation and Sampling
- ● Curse of Dimensionality
- ● Feature Selection and Creation
- ● Exercise 2
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Week 3 : Data Exploration, Data Visualization and Classification definition
- ● Data Exploration, Mode and Frequency
- ● Data Visualization
- ● What is Classification?
- ● Exercise 3
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Week 4 : Decision Trees and Neural Networks
- ● Decision Tree - Definition
- ● Neural Network Part 1
- ● Neural Network part 2
- ● Exercise 4
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Week 5 : NLP and Transformers
- ● Language Model
- ● Transformer
- ● Basic Concept of NLP
- ● Exercise 5
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Week 6 : Text mining, Clustering, Associations
- ● Text Mining
- ● Clustering
- ● Association Rules
- ● Exercise 6
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講師
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國立清華大學資訊工程系副教授 ｜ 查看講師評價
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預覽影片 & 簡介
2025 TAICA-資料探勘與應用-陳宜欣老師
<p style="text-align:justify;"><span style="color:#2e3940;background-color:#ffffff;">Data mining serves as a crucial field that leverages advanced algorithms to reveal hidden, yet invaluable insights buried within extensive datasets. These algorithms are drawn from a multitude of areas such as machine learning, artificial intelligence, pattern recognition, statistics, and database systems, working </span><span style="color:#2e3940;background-color:#ffffff;">together</span><span style="color:#2e3940;background-color:#ffffff;"> to facilitate a deeper understanding and analysis of data.</span></p><p style="text-align:justify;"><span style="color:#2e3940;background-color:#ffffff;">This course is designed for you to learn foundational knowledge needed to delve into the expansive world of data mining. Whether you are looking to enhance your skill set or expand your knowledge, this course will serve as a stepping stone to achieving your goals.</span></p><p data-start="103" data-end="517"><br /></p>