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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

4.4
417 個評分
104 個審閱

課程概述

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....

熱門審閱

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.

篩選依據:

76 - 文本挖掘和分析 的 100 個評論(共 103 個)

創建者 Rahul M

Feb 08, 2018

ok ish course. Not highly recommended, but seems fine

創建者 Watana P

Aug 23, 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.

創建者 Alex D T

Jul 23, 2017

Professor Cheng has a deep knowledge of the subject and presents a diverse topic in a very condensed set of courses. Material is well presented, but some of the quizzes and slides need to be better organized.

創建者 Siwei Y

Mar 27, 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。

創建者 Hyun J L

Nov 30, 2017

Was Quite Helpful

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 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 Guillermo C F

Oct 16, 2017

Very good course!!

創建者 Darren

Aug 23, 2017

Hope the speaker can slow down sometimes.

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

創建者 Hernan V

Sep 29, 2017

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

創建者 Aravindh

Apr 19, 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

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 Ryan L

Jul 27, 2018

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

創建者 Ian W

Aug 10, 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.

創建者 Rahila T

Nov 15, 2018

Good

創建者 To P H

May 07, 2019

Very dense content

創建者 Kaniska M

Sep 06, 2016

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

創建者 Manvendra S

Sep 05, 2017

this course is useful if you take further courses too

創建者 Gnaneshwar G

Feb 10, 2018

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

創建者 Alexandr S

Jul 11, 2019

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

創建者 Ankur B

May 08, 2019

Little outdated but still clears the basics.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

創建者 Quintus L

Nov 06, 2019

Great theoretical introduction, but not hands-on.

創建者 gayatri

Dec 13, 2016

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

創建者 Kartoffel

Sep 09, 2016

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

創建者 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