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Avis et commentaires pour d'étudiants pour Exploitation de text et analytique par Université de l'Illinois à Urbana-Champaign

4.5
étoiles
578 évaluations
128 avis

À propos du cours

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....

Meilleurs avis

JH

Feb 10, 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 25, 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.

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101 - 125 sur 127 Avis pour Exploitation de text et analytique

par Shaima M S

Jul 27, 2016

Very detailed, but taught in an easily understandable manner.

par Rahul M

Feb 08, 2018

ok ish course. Not highly recommended, but seems fine

par Rohit C

Apr 08, 2020

Text Material is good and much more informative.

par Norvin C

Oct 10, 2017

Generally quite clear explanations

par Amir Z

Sep 01, 2016

Good survey of techniques

par Savindu V K

Jul 27, 2020

Really good course.

par To P H

May 07, 2019

Very dense content

par Guillermo C F

Oct 16, 2017

Very good course!!

par Hyun J L

Nov 30, 2017

Was Quite Helpful

par Rahila T

Nov 15, 2018

Good

par 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.

par Alexandr S

Jul 11, 2019

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

par Kaniska M

Sep 06, 2016

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

par Gnaneshwar G

Feb 10, 2018

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

par Tali L

Mar 22, 2020

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

par Ankur B

May 08, 2019

Little outdated but still clears the basics.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

par Manav

Sep 05, 2017

this course is useful if you take further courses too

par Quintus L

Nov 06, 2019

Great theoretical introduction, but not hands-on.

par Alexander S

Dec 16, 2019

Course was ok. Some slides have mistakes in it.

par Leonardo P

Jun 26, 2020

Hot topic but a obsolete material.

par 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.

par 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

par Kartoffel

Sep 09, 2016

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

par gayatri

Dec 13, 2016

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

par Eugenio L C

Sep 22, 2017

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