Great course! Not simply a machine learning black box tutorial - like a few courses out there - but delves into the mathematics behind the algorithms (with several optional, more advanced excursions provided) and requires that we actually implement a few of the ideas ourselves.

Excellent combination of conceptual and practical quizzes. Providing the presentation slides is a great note-taking aid, as well as use of "ride-along" notebooks. The progressive use of the same dataset throughout the modules greatly aided focus on learning the algorithms.

Great course to get started in the Machine learning , it covers each and every concept of Regression . All the concepts are explained in so simple way that even a high school kid wont have any trouble understanding Machine learning . I would highly recommend taking this.

Absolutely loved the way Emily tackled the course content - the knowledge I gained regarding LASSO & RIdge was something even I wasn't expecting. Also the optional video helped a lot to understand the mathematics better as compared to a mechanical write-down of the steps

Fantastic course.

Lot of courses I have taken do not give the mathematical formulation. This course provides a detailed understanding of the math behind ML.

Also in the programming exercises one implements the algorithms from scratch and also use the existing libraries.

Great course! all materials are well structured and introduce each concept concisely. I enjoyed all programming assignments. Take this course if you would like to know more about regression rather than simply finding the perfect hyper-plane that approximate your data.

Emily Fox is exceptional. It's a smooth airplane ride through often turbulent paths. That's harder to do than it might seem as most teachers get mired in details that confuse and/or distract the student. I would think that any course she teaches is worth taking.

Great course, very detailed and hands on, also including appropriate amount of mathematical rigour to help you understand what is going on under the hood. Highly recommended. I specially liked the modules on Ridge regression and Lasso regression, really well done.

I found this an excellent introduction to the topic with a good mix of well-presented material and practical application using the IPython notebooks. I would love to have the course finish with a project where we apply the learned methods to a different data set.

Very responsible teachers and practical classes content.You can not only learning the ML theory from scratch,but also learn to implement the algorithm using python by yourself.This is the best ML course I ever seen.

Thanks for the teachers' hard-work.You are great!

Excellent. This is an ideal course in order to understand various aspects of regression techniques. Explanation using hands-on exercises helps me learn this course very effectively. I must appreciate the efforts of both Instructors (Prof. Emily & Prof. Carlos).

I felt that the course was detailed and contained significant in-depth study about regression techniques. The assignments were well designed, starting from a single step and eventually enabling the candidate to be able to write the complete methods on his own.

This is probably the best Coursera course I have completed so far (and I am kind of Coursera junkie). very well structured, the right amount of math and driven by the experiments on the real data.

Looking forward to Classification course and others in series.

The regression is done very well. I love the tutorials especially, they are very clear with good test feedbacks on some of the latter week contents. If you want to get into machine learning, this is a very important part to help you with all the other parts.

I liked pretty much all of the content.

The lectures are detailed.

The assignments helped me understand the techniques used in regression. The step by step approach is great.

What I dislike a bit is the promotion of proprietary and expensive Graphlab software.

A few minor glitches with the homework assignments so far. Hopefully this is only because it is the first time the class is being offered.

I love the instructors. Great enthusiasm and both clearly love what they do. Inspiring for data scientists in training.

This is a great course! The course is easily understand, the lecturers are very nicely talking in the videos to show you the knowledge of regression. The assignments are designed in a way helping you learn, practice and implement the regression algorithms.

Really exciting course. The concepts are well explained and implementing algorithms by myself is really a inspiring experience. It is really a pity that the last 2 courses in the specialization were canceled. I am even willing to pay them for 100$ each!!!!

Pretty challenging from a mathematical perspective, but extremely interesting and well-explained. I was glad to see there were plenty of opportunities to use Pandas and other Python libraries instead of just relying on Graphlab. Very happy with this class.

Excellent course. Highly recommended. Emily Fox is clear and comprehensive. In addition, this module's exercises can be fully completed using Python's Pandas sklearn and numpy libraries and without requiring the propriety GraphLab library. Good work!

Good insight into regression models. You will dive into the details of implementations of Lasso and Ridge regularization techniques. The course is actually easy to grasp for graduates with technical background, never the less gives good knowledge.

Very nice course... The instructors were really great, the explanations, the presentations, even the color schemes were all really great... Definitely one of the most fun courses I've taken at Coursera... The assignments were also well designed...

The best Machine learning course I ever took. I compare it very favourably to Jeff Leek's course, or Andew Ng's course - which are both good in their own right.

A lot of effort went into making this a really good course. I very much recommend it.

An incredibly good approach to regression. It is the perfect continuation of the introduction course, it provides very good skills to solve regression problems. I´m eager to start with the third course of the specialization after this one!

All concepts are explained really well! Knowing all the mathematics behind machine learning can never hurt, but when it comes down to actually implementing something useful it all boils down to the practicalities of the implementation.