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Applied Text Mining in Python, University of Michigan

4.2
1,453 ratings
274 reviews

About this Course

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....

Top reviews

By CC

Aug 27, 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!

By BK

Jun 26, 2018

Would love to see these courses have more practice questions in each weeks lesson. Would be helpful for repetition sake, and learning vs only doing each question once in the assignments.

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267 Reviews

By Abdoulaye Diallo

Feb 11, 2019

I'm auditing this course, as I don't have enough to get the certificate. I hugely recommend it. It's well explained.

By CMC

Feb 11, 2019

I will not say that I did not learn anything. I just wish the autograder was a little better. Basically, quite frustrating to fight a black-box grader. An example of a better autograder is the one implemented by the Princeton people for their algorithm courses.

By Alejandro Cruz Marcelo

Feb 10, 2019

The instructor provided very low quality material.

By Lucas Serrer Richter

Feb 08, 2019

The course presented a good content for beginners in NLP and I feel confident to start using what I learned in my work. But, the grader for the assignments is too slow and buggy, this should be fixed so new learners don't feel frustrated. In addition, for assignment 4, the lda trainning parameters are not viable for trainning in coursera's environment, it should be reviewed.

By Mateusz Mitula

Feb 06, 2019

Some of the topics where elaborated very briefly. There was not enough practical examples and instructor was no clear in what he was saying.

By AHMED BEN KHALIFA

Feb 05, 2019

Excellent course

By charles lenfest

Feb 04, 2019

This course was outstanding - excellent lectures, notes and examples!

By Adolfo Garza Salazar

Jan 30, 2019

Excellent course, you must to take it and work by yourself in the Assignments

By Kristin Abkemeier

Jan 30, 2019

A good intro to NLTK and text mining in Python, though sometimes the effort put in to render an assignment acceptable to the autograder was a headache.

By Lalit Suthar

Jan 29, 2019

Awesome