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學生對 伊利诺伊大学香槟分校 提供的 文本挖掘和分析 的評價和反饋

487 個評分
112 條評論


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....



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.


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.


51 - 文本挖掘和分析 的 75 個評論(共 111 個)

創建者 Hongzhi Y

Aug 01, 2016

Very practical. The lecture is easy to follow.

創建者 Christoph K

Aug 10, 2016

Very good course! Thank you :)

創建者 Sitaram

May 17, 2017

Nice course on text mining.

創建者 Viacheslav D

Dec 01, 2016

Best NLP course that I saw.

創建者 Shin, Y

Nov 15, 2016

loved all the lectures

創建者 Cheng-shuo Y

Dec 11, 2017

It is a great course!

創建者 Bang S

Mar 06, 2017

I need it ,I like it.

創建者 Luis F Y B

Sep 29, 2018

Great..Clear. Thanks

創建者 Gourav A

Oct 26, 2018

Excellent course.

創建者 David O

Jul 01, 2018

Great course

創建者 黄莉婷

Dec 27, 2017


創建者 Florov M

Apr 03, 2020


創建者 Kumar B P

May 08, 2020


創建者 R M

Apr 29, 2020


創建者 MItrajyoti K

Oct 24, 2019

Very good

創建者 Hernan C V

May 04, 2017


創建者 Arefeh Y

Nov 05, 2016


創建者 Mrinal G

May 20, 2019


創建者 Isaiah M

Jan 02, 2018


創建者 Valerie P

Jul 11, 2017


創建者 Deepak S

Aug 11, 2016


創建者 Jennifer K

Jul 05, 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!

創建者 Milan M

Sep 15, 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.

創建者 Gonzalo d l T A

May 10, 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.

創建者 Arkadiusz R

Jul 09, 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!