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

4.2
1,932 ratings
373 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

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!

GK

May 04, 2019

Lectures are very good with a perfect explanation. More than lectures I liked the assignment questions. They are worth doing. You will get to know the basic foundation of text mining. :-)

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226 - 250 of 366 Reviews for Applied Text Mining in Python

By Aswath M

Aug 02, 2019

Excellent course for someone like me who is ambitious and aspires to gain knowledge on new things. The videos can be made bit more elaborate, seems to be rushing towards the end.

By Manuela D

Aug 08, 2019

Well thought, very basic level, but a good starting point.

By Daniel J

Aug 07, 2019

It is quite a dense topic, however the instructor manages to make it much simpler.

By Ahmad H S

Aug 14, 2019

the course is good, but more practices is required

By Eric G

Aug 20, 2019

The autograder sucks!

By pavan b

Nov 19, 2018

good training

By Stephane C

Dec 09, 2018

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

By SeyedAlireza K

Dec 23, 2018

I learned some useful stuff in this course but I think it could be a little more deeper and teaching more behind theorems especially for week 4.

By Mateusz M

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 Craig A B

Nov 19, 2018

You do more work learning on your own to be able to do the projects and quizes then is given in the lectures. These University of Michigan classes aren't very balanced in terms of lectures, reading, and difficulty of projects.

By Yeifer R C

Nov 25, 2018

Is difficult, but good.

By Avi A

Jan 17, 2019

Great instructor, but the assignments are a big jump from the course notebooks in terms of difficulty. I also faced numerous issues with the autograder. In the last module, there were wrong pieces of code in the notebook and module (like ROC score being calculated from model.predict() instead of model.predict_proba()).

By Kartikey S

Jan 05, 2019

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

By Daissy D M R

Feb 19, 2019

Good topics and well explanations. A Notebook to support content of week 4 is definitely needed. More explanations in assignment for week 4 is needed. In general, week 4 lacks of organization and good content. that is why I give 3 stars instead of 5

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 Josh C

Mar 14, 2019

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

By Maha Y

Jan 14, 2019

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

By George M J

Nov 15, 2018

Good content.

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

By Muhammad H R

Feb 13, 2018

This course was just too theoretical. There were just too many lectures on the English language and nothing really practical. I learned nothing that I can actually use. There were hardly any useful text mining techniques that I learned.

By Jim S

Aug 25, 2017

Course content was informative and would benefit greatly from more depth. Some of the automated grading solutions are lacking/buggy. Excellent forum participation was key to success.

By Yahia K

Mar 24, 2018

It is an interesting course. The difficulty level is a bit high if you have never worked with text data before. The later assignments are not structured very well and in some cases the auto-grader has issues that cause correct answers to be marked incorrect. Overall, I got some use out of it.

By Tsz W K

Oct 22, 2017

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

By 陆徐超

Dec 30, 2017

Good contents, but not very clearly explained.

By James S

Feb 02, 2018

Some good stuff here, but really drops in quality toward the end and became a real slog to finish. Shame, since the rest of the specialization has been outstanding.

By Thomas P

Aug 28, 2017

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