Chevron Left
返回到 Applied Text Mining in Python

学生对 密歇根大学 提供的 Applied Text Mining in Python 的评价和反馈

3,717 个评分


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). This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python....



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.


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!


701 - Applied Text Mining in Python 的 712 个评论(共 712 个)

创建者 Michal K

Dec 16, 2021

创建者 Alexandros B

Oct 4, 2017

创建者 Alex M

Aug 27, 2017

创建者 Ji S

Apr 15, 2018

创建者 Abhishek J

Oct 10, 2020

创建者 Steven P

Feb 19, 2021

创建者 Laure C

Nov 22, 2020

创建者 naive666

Jun 29, 2019

创建者 Rodrigo L

Oct 1, 2021

创建者 christopher h

Nov 18, 2017

创建者 Maximilian W

Feb 14, 2020