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Voltar para Mineração de Texto e Análise Estatística

Comentários e feedback de alunos de Mineração de Texto e Análise Estatística da instituição Universidade de Illinois em Urbana-ChampaignUniversidade de Illinois em Urbana-Champaign

698 classificações

Sobre o curso

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....

Melhores avaliações


9 de fev de 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.


24 de mar de 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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76 — 100 de 143 Avaliações para o Mineração de Texto e Análise Estatística

por RAM K

23 de ago de 2020

excellent course

por aditya r

13 de dez de 2020

its nice course

por Raja R

22 de jan de 2021

Great Course!


16 de dez de 2020

fun learning

por Manikant R

21 de jun de 2020

great course

por David O

1 de jul de 2018

Great course

por 黄莉婷

27 de dez de 2017


por Florov M

3 de abr de 2020


por Kamlesh C

23 de ago de 2020

Thank you

por Kumar B P

8 de mai de 2020


por R M

29 de abr de 2020


por MItrajyoti K

24 de out de 2019

Very good

por 2K18/SE/129 V K

9 de mai de 2022

good one

por Hernán C V

4 de mai de 2017


por Arefeh Y

4 de nov de 2016


por Swapna.C

17 de jul de 2020


por Mrinal G

20 de mai de 2019


por Isaiah M

2 de jan de 2018


por Valerie P

11 de jul de 2017


por Deepak S

11 de ago de 2016


por Jennifer K

5 de jul de 2017

Despite the amount of material to cover, this course did a great job of introducing the right amount of detail for various aspects (motivation, algorithms, algorithmic reasoning, evaluation) on topic modelling, text clustering, text categorization, sentiment analysis, aspect sentiment analysis, evaluation of text and non-text data in context, and more. Definitely read the additional resources for the material - it will give you an incredibly in-depth view to what you learned in the lectures and also give you a start on implementing the covered algorithms on your own.

The only thing I missed in this class are assignments for implementing the algorithms in a language other than C++ and in a framework other than MeTA. It would make sense to provide this opportunity in additional, commonly-used data-science languages such as Python!

por Milan M

14 de set de 2016

This is an excellent course that captures many different text mining techniques. It requires some math knowledge in numerical analysis and probability in order to understand the concepts.

I gave 4 star rating due to 2 problems during the course:

1) Lack of examples along the formulas and principles. There are some, but many concepts could be adopted much faster if examples were introduced right along with them.

2) The optional programming exercises are easy to complete, but the environment is very confusing to set it up.

por Gonzalo d l T A

10 de mai de 2017

A really interesting course which covers theoretically most of the text mining techniques. I missed having more practical exercise, which could help to deeply understand the lectures. Setting up the environment for the development task is a little bit complicated, it might be interesting to provide a virtual machine with all the software and correct versions required. Even though, I would recommend this course if you are interested on the topic.

por Arkadiusz R

9 de jul de 2017

Very good course with a lot of essential information about problems correlated with text understanding. It give me general look for text mining topic. Some lectures give only overall information about text analysis problem, but it still gives me an opportunity to learn about these listed topics to resolve relevant problems. I recommend this course anyone!

por Fakhri A

2 de out de 2016

the course is very helpful in giving the overall flavor of text mining and analytics. I would recommend to reduce the number of math work and focus on the conceptual level along with more application that could be used. For the math part, adding optional videos for more details about math will be very useful and helpful