This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).
提供方
课程信息
学生职业成果
29%
完成这些课程后已开始新的职业生涯
32%
通过此课程获得实实在在的工作福利
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 4 门课程（共 5 门）
可灵活调整截止日期
根据您的日程表重置截止日期。
中级
完成时间大约为29 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 中文（简体）, 意大利语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 土耳其语（Turkish）, 英语（English）, 西班牙语（Spanish）
您将学到的内容有
Understand how text is handled in Python
Apply basic natural language processing methods
Write code that groups documents by topic
Describe the nltk framework for manipulating text
您将获得的技能
Natural Language Toolkit (NLTK)Text MiningPython ProgrammingNatural Language Processing
学生职业成果
29%
完成这些课程后已开始新的职业生涯
32%
通过此课程获得实实在在的工作福利
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 4 门课程（共 5 门）
可灵活调整截止日期
根据您的日程表重置截止日期。
中级
完成时间大约为29 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 中文（简体）, 意大利语, 越南语, 韩语, 德语（German）, 俄语（Russian）, 土耳其语（Turkish）, 英语（English）, 西班牙语（Spanish）
提供方
密歇根大学
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
教学大纲 - 您将从这门课程中学到什么
完成时间为 9 小时
Module 1: Working with Text in Python
完成时间为 9 小时
5 个视频 （总计 56 分钟）, 4 个阅读材料, 3 个测验
完成时间为 7 小时
Module 2: Basic Natural Language Processing
完成时间为 7 小时
3 个视频 （总计 36 分钟）
完成时间为 7 小时
Module 3: Classification of Text
完成时间为 7 小时
7 个视频 （总计 94 分钟）
完成时间为 6 小时
Module 4: Topic Modeling
完成时间为 6 小时
4 个视频 （总计 58 分钟）, 3 个阅读材料, 3 个测验
审阅
来自APPLIED TEXT MINING IN PYTHON的热门评论
由 RK 提供Jul 19, 2019
Course is great except for the auto grader issues. Please look into the issue. I would like to take this opportunity and thank Prof V. G. Vinod Vydiswaran and all those who helped me to complete it.
由 CC 提供Aug 26, 2017
Quite challenging but also quite a sense of accomplishment when you finish the course. I learned a lot and think this was the course I preferred of the entire specialization. I highly recommend it!
由 JR 提供Dec 4, 2020
Excellent course to get started with text mining and NLP with Python. The course goes over the most essential elements involved with dealing with free text. Definitely worth the time I spent on it.
由 LC 提供Feb 16, 2018
Love the focus on conceptual text processing and practical guides to implementation in python, but the assignment grader was extremely specific for no reason, especially the Week3 assignment.
关于 借助 Python 应用数据科学 专项课程
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.
常见问题
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