This course provides an unique opportunity for you to learn key components of text mining and analytics aided by the real world datasets and the text mining toolkit written in Java. Hands-on experience in core text mining techniques including text preprocessing, sentiment analysis, and topic modeling help learners be trained to be a competent data scientists.
課程信息
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立即開始，按照自己的計劃學習。
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中級
完成時間大約為19 小時
英語（English）
字幕：英語（English）, 西班牙語（Spanish）, 中文（簡體）
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
可靈活調整截止日期
根據您的日程表重置截止日期。
中級
完成時間大約為19 小時
英語（English）
字幕：英語（English）, 西班牙語（Spanish）, 中文（簡體）
提供方
延世大学
Yonsei University was established in 1885 and is the oldest private university in Korea.
教學大綱 - 您將從這門課程中學到什麼
完成時間為 3 小時
Course Logistics and the Text Mining Tool for the Course
完成時間為 3 小時
4 個視頻 （總計 53 分鐘）, 1 個閱讀材料, 1 個測驗
4 個視頻
1.2 Explanations of the y-TextMiner package and the datasets9分鐘
1.3 How-to-do: workspace installation and setup15分鐘
1.4 How-to-use: the y-TextMiner package (download it at http://informatics.yonsei.ac.kr/yTextMiner/yTextMiner1.2.zip)13分鐘
1 個閱讀材料
What is Text Mining?10分鐘
完成時間為 3 小時
Text Preprocessing
完成時間為 3 小時
5 個視頻 （總計 67 分鐘）, 1 個閱讀材料, 1 個測驗
5 個視頻
2.2 What is text mining?10分鐘
2.3 Description of preprocessing techniques11分鐘
2.4 How-to-do: normalization including tokenization and lemmatization20分鐘
2.5 How-to-do: N-Grams14分鐘
1 個閱讀材料
Text Preprocessing10分鐘
完成時間為 3 小時
Text Analysis Techniques
完成時間為 3 小時
6 個視頻 （總計 62 分鐘）, 2 個閱讀材料, 1 個測驗
6 個視頻
3.2 Explanations of named entity recognition11分鐘
3.3 Explanations of dependency parsing8分鐘
3.4 How-to-do: stopword removal and stemming14分鐘
3.5 How-to-do: NER and POS Tagging6分鐘
3.6 How-to-do: constituency and dependency parsing9分鐘
2 個閱讀材料
Stemming and Lemmatization10分鐘
Named Entity Recognition10分鐘
完成時間為 3 小時
Term Weighting and Document Classification
完成時間為 3 小時
5 個視頻 （總計 52 分鐘）, 2 個閱讀材料, 1 個測驗
5 個視頻
4.2 Explanations of document classification11分鐘
4.3 Explanations of sentiment analysis9分鐘
4.4 How-to-do: computation of tf*idf weighting10分鐘
4.5 How-to-do: classification with Logistic Regression11分鐘
2 個閱讀材料
Text Classification10分鐘
TF-IDF10分鐘
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