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Text Mining and Analytics に戻る

イリノイ大学アーバナ・シャンペーン校(University of Illinois at Urbana-Champaign) による Text Mining and Analytics の受講者のレビューおよびフィードバック



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....




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.



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.


Text Mining and Analytics: 126 - 142 / 142 レビュー

by Martin B


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


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

by Kaniska M


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

by Gnaneshwar G


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

by Tali L


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

by Ankur B


Little outdated but still clears the basics.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

by Manav


this course is useful if you take further courses too

by Quintus L


Great theoretical introduction, but not hands-on.

by Alexander S


Course was ok. Some slides have mistakes in it.

by Leonardo P


Hot topic but a obsolete material.

by Michael T


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 Vivian Y Q


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

by Peter


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

by Gayatri V


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

by Eugenio L C


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

by Shubham K


Couldnt understand a word of what the instructor said



No wayb