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.
교육 기관: Valerie P•
Jul 11, 2017
교육 기관: Deepak S•
Aug 11, 2016
교육 기관: 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!
교육 기관: 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.
교육 기관: 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.
교육 기관: 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!
교육 기관: fakhriabbas•
Oct 02, 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
교육 기관: Ahmed M S•
Jan 12, 2020
This is an excellent foundational course about text mining. It provides a very solid theoretical foundations and concepts about the subject. The only thing that felt missing, is giving more numerical examples during the video sessions to ease understanding the formulas.
교육 기관: 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.
교육 기관: Akarapat C•
Feb 12, 2017
This is a very good course. I think it provides a very good foundation of text mining and analytics like PLSA and LDA. More advanced research discussed in the last lecture is also very interesting.
교육 기관: 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.
교육 기관: 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
교육 기관: 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.
교육 기관: Darren•
Aug 23, 2017
Hope the speaker can slow down sometimes.
It will be more helpful if give more real-world examples
교육 기관: Hernan V•
Sep 29, 2017
Excellent course, but not a deep coverage of more complex text analysis algorithms
교육 기관: 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。
교육 기관: Ryan L•
Jul 27, 2018
Lots of great topics are covered. Would like to see more hands on exercises.
교육 기관: Shubhra V•
Jul 21, 2020
Very detailed course. Helps in gaining complete understanding of text mining
교육 기관: Kim C•
Jul 23, 2017
Full of intuitions about text mining. Hope I can absorb all those ideas soon
교육 기관: Tanan K•
Aug 12, 2017
Very complicated but useful for a deeper understanding of text mining
교육 기관: Jan-Henk P•
Jun 06, 2020
More examples/questions during the course in using the formulas
교육 기관: Shaima M S•
Jul 27, 2016
Very detailed, but taught in an easily understandable manner.
교육 기관: Rahul M•
Feb 08, 2018
ok ish course. Not highly recommended, but seems fine
교육 기관: Rohit C•
Apr 08, 2020
Text Material is good and much more informative.
교육 기관: Norvin C•
Oct 10, 2017
Generally quite clear explanations