Отзывы учащихся о курсе Анализ текстовой информации и аналитика от партнера Иллинойсский университет в Урбане-Шампейне

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.

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

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.

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

Hope the speaker can slow down sometimes.

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

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

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。

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

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

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

Very complicated but useful for a deeper understanding of text mining

More examples/questions during the course in using the formulas

Very detailed, but taught in an easily understandable manner.

ok ish course. Not highly recommended, but seems fine

Text Material is good and much more informative.

Generally quite clear explanations

Good survey of techniques

Really good course.

Very dense content

Very good course!!

Was Quite Helpful

great course

Good

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.

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