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

4.2
1,978 ratings
380 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

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. :-)

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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176 - 200 of 373 Reviews for Applied Text Mining in Python

By Charles F

Sep 20, 2017

The course content is very interesting and high quality; however, the video slides include code that is not available in e.g. jupyter notebooks. Also, the assignment markers do not give any useful feedback - more than half of the time spent was usually when 99% of the task was complete but some very minor detail threw the marker off.

By Oscar J O R

Sep 02, 2017

Nice introduction to the topic and interesting tools. The evaluation system could be improved adding more resources focused on the use of the nltk functions or giving some advice about the critical points in the Python demonstrations.

By Han C

Sep 01, 2017

Learned lots of new stuff, but some details are not established well including autograder issue at the last assignment. Hope this gets cleared out soon.

By Leo C

Feb 17, 2018

Love the focus on conceptual text processing and practical guides to implementation in python, but the assignment grader was extremely specific for no reason, especially the Week3 assignment.

By Carl W S

Sep 01, 2017

Overall, a solid course, though it felt a bit like a face-to-face lecture course recorded to video. The material was helpful and well-explained, but I feel it could benefit from taking advantage of the MOOC medium more effectively, such as by providing code sample notebooks for the students to run and modify, which have been very helpful to me in understanding the material in other courses in the same specialization.

By Traci L J

Dec 07, 2017

I learned a lot about regular expressions, how to use NLTK to parse words and parts of speech, and to apply machine learning techniques from the third course to text.

The homework assignments were finicky with the autograder and often there was a lot of frustration regarding the exact data types of the output. I spent a lot of type debugging over simple things that could have been clarified in the assignment description. However, the discussion forums are active and people are willing to give feedback!

By João R W S

Aug 23, 2017

Very good course with very good material and teachers. I just missed some more practical examples to follow along the classes, and more further readings (specially for information extraction).

By Iurii S

Feb 10, 2018

overall a goods intro into text analysis

By Abe G V T S

Oct 05, 2017

The class was great. However the assignments had a lot of problems.

By Yang F

Aug 23, 2017

Useful topic.

By Niels R

Apr 24, 2018

Overall this is well done course, but the autograder for week 2 needs a lot of work. It was buggy, broken and gave uninformative answers.

By Girish G

Nov 20, 2017

Awesome course..It is a good start for NLP. Comprehensively covers all topics. The Autograder for the programming assignment needs

By Kunal c

Aug 10, 2017

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

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 Mykhailo L

Jan 03, 2018

Good intro course on NLP

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 Anad K

Jun 17, 2018

Content-wise course is okey. But all the students faced issues during the assignment submissions because of the auto grader.

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 Vinicius G

Dec 26, 2017

I did not give 5 starts because Assignment 4 was really hard. It required too much knowledge from outside. The week 4 modules poorly prepared me for assignment 4.

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 Чижов В Б

Dec 18, 2017

It is interesting, cognitive and very useful. But, there were very few answers from the teaching staff in the discussions at the forum. In previous courses of this and other specializations, the teaching staff took an active part in the forum and this greatly helped in understanding and fulfilling the tasks of the course.