Oct 16, 2016
Hats off to the team who put the course together! Prof Guestrin is a great teacher. The course gave me in-depth knowledge regarding classification and the math and intuition behind it. It was fun!
Jan 25, 2017
Very impressive course, I would recommend taking course 1 and 2 in this specialization first since they skip over some things in this course that they have explained thoroughly in those courses
by Richard L•
Oct 15, 2016
Great course. The lectures and programming assignments have been extremely beneficial to help me get a basic foundation of ML classification.
by Fan D•
Feb 02, 2017
This course is alright. For some reason I liked the regression course more as this one was a little to simple in terms of the practical.
Nov 17, 2016
Course is really good. Assignments are taking too much time if you want to do the course rally fast, with questionable learning value.
by Sergio D H•
Jul 22, 2016
AWESOME COURSE!! Carlos and Emily are incredible teachers and the course contents are truly informative and well-paced for beginners.
by Nitin D•
Dec 18, 2018
Excellent lessons on this important topic Classification. I think all major areas were explained quite nicely, with proper examples.
by Dongliang Z•
Mar 22, 2018
Excellent course! The teacher explained a lot of intuitions during the course. The optional part s are very interesting and helpful.
by Ornella G•
Oct 01, 2016
I really enjoyed the topics presented and the fluid way to present them. It's a very well done summary of the classification models.
by Siddharth S•
Jan 09, 2018
Excellent course and all the concepts have been explained very simply and with an element of fun.
Many thanks to Emily and Carlos...
by Gaurav C•
May 22, 2019
Would have loved even more had Carlos explained his students gradient boosting as well. I liked the way of his taught in lectures.
by Ankur P•
May 29, 2018
Loved the way our tutor (Carlos) explained the concepts to us. Things are getting clearer with each course in ML :) Many thanks :)
by Renato R S•
Aug 27, 2016
All the basics - and much of the advanced stuff - is presented, in a coherent and inspired way. Thanks for crafting such a course.
by Joseph F•
Apr 05, 2018
Good course with many assignment to design the algorithm with your own code. But I think this course last a little bit too long.
by Reinhold L•
Mar 21, 2019
Very good course for classification in machine learning - top presentation documents - very well structured and practical
by Pawan K S•
May 15, 2016
Nice course with appropriate amount of detail in it! Covers tough mathematical aspect for those who are interested in it.
by Fabio P•
Apr 18, 2016
Very interesting topic with some advanced topics covered. It really shows how to use machine learning in the real world.
by Vibhutesh K S•
May 22, 2019
It was a very detailed course. I wished, doing it much earlier in my research career. Great insights and Exercises.
by Igor K•
Mar 16, 2016
very interesting and novice friendly, however some math (basic matrix calculus and derivatives) review worth doing
by Etienne V•
Nov 13, 2016
Great course with very good material! I'd like to see assignments that leaves more coding tasks to the student.
by Naman M•
Jul 09, 2019
you can't find a better course on machine learning as compared to this one. Simply the best course on coursera
by Naimisha S•
Jul 30, 2018
Availability of the Ipython notebook makes it easy to solve the Quizzes which has step by step explaination
by Konstantinos P•
Mar 28, 2017
The context and the structure of the course is absolutely perfect. Also, Carlos is the perfect professor!
by Hristo V•
Dec 01, 2016
The course is absolutely amazing! Very clear explanation of the concepts with great notebook assignments.
by Shaowei P•
Mar 31, 2016
great course, would have been even more great if there are more details on how to use boosting for kaggle
by Rashi K•
Mar 17, 2016
Assignments were more challenging than previous course. Loved solving them. Enjoyed the optional videos.
by Dmitri T•
Apr 25, 2016
Really liked the practical application of this course - very useful in learning classification methods.