I definitely learned a lot in this class about different techniques and ways to use regression in machine learning. I also feel like I learned a lot about how to program in Python.

I like the step-by-step introduction that familiarize one with the important concepts. I also like the nice explanation and visualization of some relevant mathematics. Recommended.

thorough explanation. they cover most of the topics. lessons on ridge and lasso regression are great. would recommend for anyone looking to get into data science/ machine learning.

Great course covering Regression Machine Learning. Gives a great introduction to this topic. Teaching the methods using a case study yields for great illustrations of the concepts.

This course is damn well structured. Course material is great and programming assignments are interesting and helps you to really understand how to implement regression algorithms.

The professors help understand the concepts from ground up. Seriously recommended course if you want to know how Regression works and all about ridge, lasso and kernel regression.

The course goes into great details to clarify difficult concepts. Besides, the assignments are well designed so that students can grasp the topic step by step through practicing.

Thorough introduction to regression, the assignments are demanding, and the teachers very engaging. It would be nice if a wider range of applications and examples were presented.

Very good course with nice slides and clear interpret, and the assignment with ipython is really well designed because it already give you the illustration of each step. Thanks!

You will get a good grasp of Linear Regression, Ridge Regression, Lasso and potential use for feature selection, gradient descent, coordinate descent, numpy and graphlab create

Goes well beyond the statistics that I learned in engineering! Key concepts in regression such Ridge, Lasso and KNN. Use Python to build all your algorithms from the ground up.

it gave more details than my class room. it also adopts a practical approach to learn. it is a great course in regression especially for practitioners.

Thanks Carlos and Emily :)

Great course on Regression. This will help build basic for upcoming modules. Emily teaches the concepts in a simple way. I liked the structure and coverage of Regression topic.

Great material, this was tougher than the previous course. It is challenging and more exercises to practice which help to a better understanding of the concepts. Great mentors!

An extremely well designed course, I am an instructional designer myself, so adding weight to the words. Would have appreciated a few more assignments for the last week though.

I feel I understand regression models better than before. But I still need to read more books on the same topic to actually convert what I learned here to long term memory :)

Fantastic Course, allowed me to gain insights to regression. Both the instructors like always have been excellent. Shout out to coursera for allowing me to take this course!

It's a really nice course.What i've learned in this course: how to implement a regression model through my own hands, assessing performance, feature selection...and so on.

This course is very well organized and all the information is relevant. Everything is explained in great detail. The exercises really make you feel that you are learning.

All the courses in this specializations are very well-made and rigorous. I think all MOOCs, especially techinical ones, should be as well-designed as this or even more.

The course is really helpful. It has started with simple Regression model and gradually build the different advance regression model. Thanks for this wonderful course.

rigorously explained some of the most important algorithms in regression world, also the pros and cons of using certain algorithm for certain conditions. totally worth

Good overall theoretical and practical explanation of the material, I was also able to use scikit learn and pandas without any difficulties instead of graphlab create.

Great class (really liked the graphical interpretations of Lasso and Ridge optimizations).

Perhaps some quizzes (and especially assignements) could be more challenging?

Great course, excelent professors & simple yet accurate explanations, always guiding you through the course and through practical implementation of acquired knowledge