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

4.2
2,112 ratings
396 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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151 - 175 of 389 Reviews for Applied Text Mining in Python

By Ankit G

Nov 18, 2018

basic and nice course

By Lalit S

Jan 29, 2019

Awesome

By Kristin A

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 bictor

Nov 06, 2018

Very interesting

By Vo C C

Nov 09, 2018

The assignments are a little hard and have some errors, but the overall explanation is awesome.

By Lucas S R

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 CaitlinYao

Feb 17, 2019

The assignments are much harder than the slides, which means much more self-learning is required.

By Roberto L L

Mar 01, 2019

This an excellent course to open a door for NLP, an exciting topic.

By Muhammad S J

Mar 08, 2019

Overall course is very usefull for me. But there is lot of detail is missing in week 4. Wordnet and Gensim usage, Detail about the LDA and semantic similarity. I hope next time there is separate video lecture for detailed about Semantic simalarity.

By Alexander G

Jan 13, 2019

It would help to connect the teaching better to the assignments. Especially in Week 4 there is to little connection. There is not even a course notebook to practice some of the material.

By Rahila T

Nov 15, 2018

Good

By Utkarsh T

Dec 18, 2018

NA

By Michael M

Mar 22, 2019

Great course. Auto graders have some issues.

By Frank L

Oct 14, 2017

Was very detailed and well taught

By Patrick L

May 26, 2018

Great course, didn't expect to get so much value out of it. Sometimes the instructions in the assignments are unlear though.

By Aleksey B

Mar 08, 2018

Some assignments were very ambigues - namely part One of final assignment.

By Nicolas B

Aug 26, 2017

Great course, could improve the last week with more practical examples.

By Christos G

Aug 22, 2017

This was a very well thought and assembled set of Text Mining applications in Python. The complexity and profoundness of the topic somehow prohibited the instructors from sufficiently explaining the details in some occasions, which might eventually cause frustration with the students. However, perhaps this wide-first approach versus the deep dive is preferable for the purpose of the course. In all cases, Google and Stackoverflow will always remain as last resorts and supporting information sources.

By Sebastian H

Mar 18, 2018

The course is quite interesting and you learn the basic concepts and tools.

The programming assignments were sometimes unclear in the formulation of the tasks. Additionally the autograder seems to be a bi buggy, which was very frustrating and cost me a lot of time.

But, thanks to the vivid and helpful discussion forum in the end it is feasible.

And since you learn the most out of all this little hurdles ;) , the course is still very valuable!

By Fedor K

Nov 16, 2017

G

By cheting c

Jun 22, 2018

Overall good class but the assignment design is somehow bad. Should give some hint otherwise we do not know if we get a wrong answer or the autogarder is not working.

By Saber D

Jan 17, 2018

Very useful course to text mining.

By Aditya R

Oct 05, 2017

Good Course

By Kunal c

Aug 10, 2017

There were certain issues with the autograder. But the course content was good

By Jeremy L

Oct 26, 2017

The course itself is good, but the assigment system is not robust and some sentences are also ambiguous to users. Seeing from the forums, many users get confused in the assigments.