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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
660 évaluations
141 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
9 févr. 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
24 mars 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 140 Avis pour Exploitation de text et analytique

par Watana P

22 août 2017

Most of the lessons are mathematical formulae in which, in my opinion, I need more real case study/practice to make myself clearly understand on how do those formulae perform.

par Aravindh

19 avr. 2017

The content is really good but the course has too much theory. Mixing it with some practical programming assignments would have been very nice

par Ian W

10 août 2018

In-depth description on the algorithms.

Personally I suggest finish the quiz of the nth week after finishing all the video of (n+1)th week.

par Cihan T

5 nov. 2020

Nice course for the people who want to acquire knowledge about mostly the theoretical part of certain NLP methods.

par Darren

23 août 2017

Hope the speaker can slow down sometimes.

It will be more helpful if give more real-world examples

par Hernan V

29 sept. 2017

Excellent course, but not a deep coverage of more complex text analysis algorithms

par Siwei Y

27 mars 2017

老师选择的课题非常丰富 , 讲解的逻辑脉络也非常清晰, 这是许多所谓的大牛教授所无法做到的 。

只是不知道为何, 论坛太过冷清, 里面似乎也没什么 人负责解答问题。

par Ryan L

27 juil. 2018

Lots of great topics are covered. Would like to see more hands on exercises.

par Shubhra V

21 juil. 2020

Very detailed course. Helps in gaining complete understanding of text mining

par Kim C

23 juil. 2017

Full of intuitions about text mining. Hope I can absorb all those ideas soon

par Tanan K

12 août 2017

Very complicated but useful for a deeper understanding of text mining

par Jan-Henk P

6 juin 2020

More examples/questions during the course in using the formulas

par Shaima S

27 juil. 2016

Very detailed, but taught in an easily understandable manner.

par Rahul M

7 févr. 2018

ok ish course. Not highly recommended, but seems fine

par Rohit C

8 avr. 2020

Text Material is good and much more informative.

par Norvin C

10 oct. 2017

Generally quite clear explanations

par Amir Z

1 sept. 2016

Good survey of techniques

par Savindu V K

27 juil. 2020

Really good course.

par To P H

6 mai 2019

Very dense content

par Guillermo C F

16 oct. 2017

Very good course!!

par Hyun J L

29 nov. 2017

Was Quite Helpful

par PRANAV N

18 mars 2021

great course

par Rahila T

15 nov. 2018

Good

par Martin B

26 sept. 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

11 juil. 2019

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