Good survey of techniques

Thanks for this course.

Nicely explained

Good Experience.

Was interesting

Good

good

Good

G

I got the sense that this course needs to be updated. Some of the quizzes covered work that had not been treated up to that point and the programming assignment did not work with the most recent version of the MeTA toolkit. For a course of this stature I would have expected a lot more attention to such detail. It would also appear as though the owners of the course material are not present on the forums with students left to their own devices.This course as well as the Text Mining one does not compare well with the Machine Learning course from Stanford offered on Coursera when considering the above issues.Some work is required I believe

The course was great. What I had a real problem with was the lack of response for problems with the Honors programming assignments. I never received any feedback from the TA's and when I submitted to MeTa support, they said the school design the programs so they can't help. I got a Segmentation Fault on Assignment one which I never did get resolved. Because of this, I was unable to get the Honors status.

The course conveys a lot of well-structured content. The theoretical concepts are taught well by the videos, although some videos are a little bit too long.

Unfortunately, I was not able to do the practical assignments due to technical problems with the installation of the required development environment. I missed experiencing in practice what I have learnt in theory.

Lectures are fine for those who does not want to read a book and want to get a quick overview. Quizzes are very un-useful and buggy. There are questions presented that are not covered in the section. Programming assignments are optional because instructor did not want to adapt them for Coursera format so that they can be completed using tools of choice.

The course does not give much of practical knowledge, mostly theoretical. For example, presented material does not teach you what is required to build a good search engine. Even theoretical part is mostly based on old view, which is proven to be not working. For some topics the exam was given before the topic was presented in lectures.

Very theoretical and somewhat dry. If you are interested in applied machine learning techniques (for text retrieval and analysis) this is not really the course to take. Gives a solid background though which, in my opinion, every aspiring data analyst needs.

Essentially a very interesting and well structured course. Unfortunately, its honours track programming assignments are plagued by technical issues, and there are inconsistencies between the schedule of the video lectures and what is asked in the quizzes.

Some courses lack lecture notes. There are some mistake in the week exercise (some question regarding topic in wk5 appears in wk4). So the overall feeling for the course is not well considering it is a part of the school's graduate program

The quiz content is out of sync with the lecture content and has not been fixed after what appears to be 2 years of comments in the course error message board and weekly discussion boards.

The course topic is very interesting but i found some difficulties to follow up some lectures. I had a concern alson on quizzes; some of them is not related to the current week.

excellent material and great explanations! The main problem here is that quizzes will sometimes cover subjects not introduced until the following week.

Concepts are not much clear. I think the equations should be explained with some real life problems and not just general idea.

Ok. It was a rerun and there wasn't much help in the Forum and there were too few exercises. But it was really interesting.

Interessant, but it wasn't organized too well. Some questions referred to topics which came in the next lesson

Heavily focused on formulas. I prefer courses which focus on basic concepts more.

Too much theories ,I hope the professor add more programming assignment.