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

4.2
stars
3,784 ratings

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

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!

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.

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626 - 650 of 737 Reviews for Applied Text Mining in Python

By Alexander W

Sep 3, 2019

This course is interesting and about a very important topic, but it urgently needs an update!

By Tsz W K

Oct 22, 2017

Less organised to the previous three courses. However, it still introduces useful techniques.

By Ling G

Aug 31, 2017

I like the lecture very much. If the lecture can cover more example codes it iwll be greater.

By Thomas P

Aug 27, 2017

Good course content, but no in-depth discussion of topics. Assignments are also very buggy.

By Paula C R

Aug 4, 2017

I think the course was superficial and could be better explored. It's good start, though.

By Shubhankar M

Dec 25, 2020

It is an important course but instruction felt incomplete while doing the assignments.

By Josh C

Mar 14, 2019

The contents are good, but the online autograding system really need to be improved.

By Kartikey S

Jan 5, 2019

Some topics are hastily explained and maybe more content was needed in this course.

By Stephane C

Dec 9, 2018

Week3 and 4. Too much of strange bugs with the auto grader. Not enougth examples...

By Vicente P

Jul 29, 2019

I think the course need a better speaker and more notebook hours to be enhanced.

By Maha Y

Jan 14, 2019

Need to show the slides for longer in the videos. But good learning experience.

By Qian H

Oct 3, 2017

The homework is quite not related to the lecture. And it is so hard to finish.

By Eric S

Sep 27, 2018

Most assigmets were not in the notes. Still everyhting seems really usefull.

By Raivis J

Aug 11, 2018

Graded assignments need more grounding in practically applicable situations.

By George M J

Nov 15, 2018

Good content.

Had to spend way too much time fighting the auto-grader.

By Zhizhong S

Jan 7, 2021

The course is not well organized comparing with the other four.

By CARNEMOLLA B

Jul 8, 2019

Contenuti troppo superficiali, gli assignment troppo specifici

By Gennadiy D

Oct 21, 2017

I will be better to provide python code in a separate notebook

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 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.