Learner Reviews & Feedback for Machine Learning: Regression by University of Washington

Useful to get a first understanding but do not feel comfortable to use any of it in real case scenarios. Could give solutions at the end of the whole course to see best coding, and unsolved questions.

It would have been nice to have some videos devoted to inference on the model coefficients and statistical model comparison, or on how adding/removing features can be assessed from such point view.

Programming assignment sometime ambiguious and hard to follow. A lot of time you have no idea WHICH dataset they are talking about e.g. "query house" in the last lesson.

Overall it's a great course.

This course start from problems. So this great to motivate the content and let student know why. However, there are lot of confusion questions that lead to miss understand the exercise problems.

I appreciate the nuts and bolts focus on implementation that facilitates development of intuition, intuition that for me at least does not come from presentation of the mathematics in isolation.

This is an excellent course to get the math involve behind the regression. Instructors are awesome. I also feel that Bayseain regression should have been included. I missed that part badly.

when quizs get harder, i'd hope we have more intermediate numbers that we can use to verify with my results. instead of every 5 or 10 steps, maybe it's good to have one every other step.

Very challenging course. Could have been 5 had the course duration been stretched by 2 weeks.

Tough to complete and do justice to the subject matter in the time frame provided.

Really well presented. Good mix of theoretical and practical. Also, excellent intro course for those with statistics background getting into the machine learning arena

Some questions in the quiz, regarding the speed needed is not explained in the course. The course gives orders of magnitude while the quizes ask for he exact estimation

Assignments were not challenging, I think they could be made harder. The instructor is awesome, though: she is very clear and dives in satisfiable depth on each topic.

The lecturer is a very skilled presenter that it's difficult to get bored watching the videos. The partially completed code is a great idea, too. Enjoyed this course!

In my opnion this course offers a good overview of regression fundamentals and techniques. Like mentioned in the course inference is a topic that is missing.

Nice Course, every concept was explained in necessary details, the quizzes should include questions which should be inferential rather than only output based.

A lot of new concepts were introduced with good clarity. All the math was less rigorous which was perfect to understand and get hold on important techniques.

Excellent course to take a deep dive into Regression concepts. Could have been better if the hands on part would have been in R - Programming as well.

Amazing course, with focus on both theory and application part.

Only problem was the use of GraphLab, would have been lot better if pandas was used

Fue un buen curso, pero noté que a veces cambiaban las fórmulas y no explicaban el porqué. Eso me causó mucha confusión y algo de tiempo perdido.

like it so far, after one week

i like the way they let us code the procedures ourselves.

expect it to level up in the upcoming weeks and classes

Excellent materials. I don't agree with some of the programming principals, but the ML stuff is spot on and I'm using these lessons daily.

Excellent series of courses. Before this was confused what was my interest in Computer Science, now I've found Machine Learning, perfect.

I think you should make update process of Graphlab more intuitive, this was the only problem I have faced during this wonderful course!

Better deep understanding of common machine learning concepts. Still learn some different things than those exposed on andrew ng course

Well, I think Carlos teaches way more enthusiastically and energetically than Emily! But I did enjoy my course on this specialization.

I think the forum activity is a bit low, and I think in some cases the things are overly describes whereas in others it goes too fast.