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Learner Reviews & Feedback for Applied Text Mining in Python by University of Michigan

4.3
stars
3,474 ratings
668 reviews

About the 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

JR
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.

CC
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!

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551 - 575 of 659 Reviews for Applied Text Mining in Python

By Ibadurrahman

May 25, 2020

the assignment was painful (the question is not very clear)

By Benjamin C

Jan 2, 2020

Good course overall but necessary upadates are lacking.

By SHIVANGI N

Sep 10, 2020

More of practical implementation should be included

By ETC_BE_A_19_Nilesh_ C

Jun 1, 2020

Topic Modelling should be explained in more detail.

By Vasilis S

Sep 1, 2018

Poor ability from lecturer to explain key concepts.

By Valeriya P

Aug 28, 2017

the course is ok, should be more technical though.

By Alonso G L

Apr 11, 2020

Very exciting topic, but not so exciting course.

By ERNESTO L C

Nov 8, 2020

Its ok but was the worst of the specialization

By 陆徐超

Dec 30, 2017

Good contents, but not very clearly explained.

By Lavanya

Jul 5, 2020

programming assignments are too technical

By Ashwini B

Jun 3, 2018

Topics like LDA need better explanations.

By Navjyot W

Jan 18, 2020

The assignments were a little complex

By Joan P

Nov 7, 2017

A lot of issues with the auto graders

By Dhanush P

Apr 25, 2020

Last week is not properly thought

By Imran A G

Sep 24, 2018

Good for basic understanding only

By Abhijit K

Jun 8, 2020

More Hands on is required on it.

By Silvia

Apr 24, 2018

Assignments were too difficult.

By Georgios P

Oct 30, 2017

Week 4 was not sufficient

By Yeifer R C

Nov 25, 2018

Is difficult, but good.

By Sara C

May 16, 2018

I like the lecturer.

By Xuening H

Jan 31, 2020

Bad autograder

By pavan b

Nov 19, 2018

good training

By Aditya M

Jul 21, 2020

nice

By Alperen B O

Dec 16, 2020

bad

By Peter B

Jul 11, 2018

I have major qualms with this course. So far in the specialization, this course is certainly the worst. *The autograder is terrible, having had serious, known issues for 8+ months at the time of this review.*The course content is incorrect, teaching learners the incorrect way to calculate roc_auc_score. *The course blows through certain topics, like Part-of-Speech tagging & Parsing sentence structure, leaving learners like myself without a good overview. I don't even have a good set of links to learn more. I can run a few commands and understand why it might be important, but I have no idea how to use it in practice. *Unlike other courses in the specialization, this one doesn't have good links to interesting academic papers or real world applications.*Unlike other courses, every week does NOT include a weekly Juptyer notebook.Here's a simple solution - give Uwe, an excellent and active Mentor, the permissions to fix this broken course. On the plus side: the instructor is ok, the topic is interesting, and this course really only feels terrible relative to the excellent courses in this specialization. I can still hardily recommend the specialization...