Very well done course.

Would be nice to have many more very short examples during the lectures that match the formulas. This would help me understand the formulas much better since I do not have a calculus or linear algebra background.

Excellent and intuitive introduction to classification.Certainly a lighthouse in a rather overwhelming and chaotic learning scenario of machine learning we have now a days(Highly recommended for both mathematics and programming student)

This course covered very interesting aspects of real-world applications for machine learning. From my point of view, the theory was very clear an valuable, until that point that the programming assignments closed the cycle beautifully.

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

Really awesome course. Nice balance between practical uses, theory, and implementation projects. It's good they kept the "optional" videos for the more detailed discussion instead of just removing that material. Totally recommend it.

An interesting series of Lectures in the important topic of Classification. The business case approach followed by the instructors provides great help to apply the required theoretical knowledge and further elaborate these methods.

Challenging and Exciting Course. Lots of ML concepts (Decision Trees, AdaBoost, Ensembles, Stochastic gradient, loglikelyhood etc. ) are introduced and i believe this course is of extreme importance in laying the fundamentals of ML.

The course is well designed for both beginners and experts . The concepts are well explained and the assignments are really challenging. Best thing is , it talks more from practical aspects . The optional sections are really good.

The best course I could find to get a strong hold of the basics of machine learning. Presented in very easy to follow steps with thorough coverage of all the concepts necessary to understand the big picture of each algorithm.

very useful course : covers a range of very practical and useful topics I had heard about but didn't fully understand until taking this course. Some highlights stochastic gradient, boosting, and precision-recall trade offs.

After watching Emily's Fox Regression wondered how much better could this professor be...But Mr Guestrin is truly great. Fantastic job, well explained difficult concepts. Probably the best classification course out there

very good course

very good and intelligent instructor

overall very good content and passion course i had learned a lot

very good and awesome efforts by instructor carlose guestin well done

very happy with this course :)

This specialization overall is pretty good. Personally I feel like Classification talks more about concepts and important ideas and requires less on coding comparing to Regression. Learned a lot! Love Carlos and Emily!

Very nice course for beginners to enhance the knowledge.. Thanks to Resp. Sir for your clear view for each concept which helps me lot. Thanks to Team & university of Washington.. Really enjoy the study in each module.

One of the best online machine learning courses I have taken. Excellent explanation of many techniques on Classification. A great combination of theory and hands-on examples. Thank you, Professors Fox & Guestrin.

Curso excelente, desde o material, as atividades práticas e aulas. O fórum de discussões é repleto de pessoas interessadas em ajudar. Essa é a especialização a longa distância definitiva de Machine Learning.

Informative with useful assignments and optional lectures that provide a deeper mathematical understanding. Great for newbies as well as more seasoned computer scientists looking to expand into new material.

A very deep and comprehensive course for learning some of the core fundamentals of Machine Learning. Can get a bit frustrating at times because of numerous assignments :P but a fun thing overall :)

Great course!

Personally I could use a little more on the math behind the algorithms (e.g. Adaboost, why does it work?).

Also, would be great to add SVM in next iterations of this class.

Thanks!

The way Carlos Guestrin explains things is exquisite. if basics is what is very important to you, and can learn code implementation and libraries from other sources, this is the go to course

I enjoyed this course a lot. The case study approach and the optional videos are full of intuitions and I love the way instructors put across the concepts very clearly ... Thank you so much

All courses in this series are organized and taught in an extremely efficient manner. I have learned so much out of them and they have helped me with my current job and my next job search!

Very thorough and engaging. Optional material allowed the more curious to learn a great deal about the topics. Simple, hands-on approach to classification algorithms. Highly recommended!

A very good course, with effective intuitive explanations of what the algorithms are supposed to achieve and how. The exercises in Python help understand the topic and fix it in memory.

A bit easy to get through the exercises bur otherwise a very enlightening and inspiring course. - This is btw a positive review if anybody should be in doubt after taking this course :)