Chevron Left
Back to Text Mining and Analytics

Learner Reviews & Feedback for Text Mining and Analytics by University of Illinois at Urbana-Champaign

4.5
stars
721 ratings

About the Course

This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort. Detailed analysis of text data requires understanding of natural language text, which is known to be a difficult task for computers. However, a number of statistical approaches have been shown to work well for the "shallow" but robust analysis of text data for pattern finding and knowledge discovery. You will learn the basic concepts, principles, and major algorithms in text mining and their potential applications....

Top reviews

JH

Feb 9, 2017

Excellent course, the pipeline they propose to help you understand text mining is quite helpful. It has an important introduction to the most key concepts and techniques for text mining and analytics.

DC

Mar 24, 2018

The content of Text Mining and Analytics is very comprehensive and deep. More practise about how formula works would be better. Quiz could be not tough to be completed after attending every lectures.

Filter by:

126 - 146 of 146 Reviews for Text Mining and Analytics

By Guillermo C F

Oct 16, 2017

Very good course!!

By Hyun J L

Nov 29, 2017

Was Quite Helpful

By PRANAV N

Mar 18, 2021

great course

By Rahila T

Nov 15, 2018

Good

By Martin B

Sep 26, 2020

This course is a mixed bag. The instructor is precise and to the point. It covers quite a few techniques that are usually not covered in other machine learning courses and offers good suggestions for additional reading to get into specific technical details. There are however two main drawbacks. First: there is only a single optional programming assigment in C++. Learning materials like these is often more thorough with programming assignments attached to them, which is the case in all of the best courses in the field of Machine Learning or Data Science. Second: the instructor's English is not great. This makes the course difficult to follow sometimes, especially since the automatically generated subtitles tend to be VERY bad and occasionally misleading.

By Alexandr S

Jul 11, 2019

The Professor has a difficulty with English pronunciation, so sometimes it is very hard to understand his speech.

By Kaniska M

Sep 5, 2016

The coding assignment instructions are near impossible to follow. The lecture is monotonous in the later weeks.

By Gnaneshwar G

Feb 10, 2018

Its was alright. The author must try different approach or explain a bit more about the mathematical equations

By Tali L

Mar 22, 2020

Awesome content. However, the lectures were slow and many were longer than I thought they needed to be.

By Ankur B

May 8, 2019

Little outdated but still clears the basics. More theoretical and less programming based

By Manvendra

Sep 5, 2017

this course is useful if you take further courses too

By Quintus L

Nov 6, 2019

Great theoretical introduction, but not hands-on.

By Alexander S

Dec 16, 2019

Course was ok. Some slides have mistakes in it.

By Leonardo P

Jun 25, 2020

Hot topic but a obsolete material.

By Michael T

Sep 22, 2016

Forums were poorly organized and not well participated in.

There was no forum topic for the honors assignment.

Honors assignment appeared to require unix, which was not stated in the course requirements.

Honors assignment was due too early in the term.

By Johann Q

Mar 24, 2024

Very complex topics with average teaching skills. There is always a weird background noise, sounds like a notebook fan, that distracts me. Course is also to long.

By Vivian Y Q

Aug 11, 2017

it is really dry. Not hands on at all. Not everyone knows c, would appreciate more approachable hands on experience

By Peter

Sep 9, 2016

Too much theory, not enough practical exercises and too few examples of how the algorithms work.

By Gayatri V

Dec 12, 2016

Could not understand many of the mathematical formulae involved. The topic coverage was good.

By Eugenio L C

Sep 22, 2017

While interesting, the videos are too long, and few practical

By HARSHWARDHAN I

Jun 13, 2020

No wayb