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 João F A d S•
Apr 18, 2016
Very good content, very well explained... great course. Classification its a very broad topic but i think this is great introduction.
The hands on where kinda on the easy side... but very interesting.
by David F•
Aug 07, 2016
Not as good as the previous courses in this specialization - I agree with those who have noted that this one seemed a little rushed. However, these are still the best courses I've found on Coursera.
by Ahmed N•
Feb 23, 2018
Great knowledge about machine learning fundamentals, More math illustration needed though it's great knowledge and very great basics about different machine learning algorithm used in reality
by Eric M•
Apr 15, 2017
Extremely clear and informative. Good introduction to ML. I felt the labs could have had us write a little more of our own code, and would have been better to use non-proprietary libraries.
by Dawid L•
Mar 20, 2017
Presented content is rather clear and instructors are rather easy to follow. Only the assignments are often confusing as there are questions which refer to missing content.
by Thuc D X•
Jun 28, 2019
Sometimes the assignment description was hard to follow along. Overall, the course equips me a good understand and practical skills to tackle classification tasks.
by Gaurav K J•
May 01, 2018
I learnt a lot, but I feel course 2 was very well made and this one felt a bit unstructured in comparison. Also, assignments in this course were made very easy.
by Justin K•
Jun 10, 2016
Assignments were a little too easy, considering that students are expected to have taken the first two courses in the specialization. Otherwise, great course!
by Hao H•
Jun 12, 2016
Good course overall. Some difficult materials such as boosting were not clear enough and I had to look into a few online resources to really understand it.
by Brian B•
Apr 22, 2016
Great course. I'm really looking forward to learn more about clustering in the next course since I know nearly nothing about clustering.
by Fahad S•
Nov 03, 2018
The content was excellent and the exercises were really good. It would be better if svms and bayesian classifiers are also covered
by Alexis C•
Sep 29, 2016
wanted more sophisticated mathematics and intuition (as opposed to simpler explanations). [regression course had this ...]
by Kishaan J•
Jul 01, 2017
Really loved this course! The insights into decision trees and precision-recall couldn't have been any better! Thank you!
Aug 19, 2017
Wanted some stuff on SVM and Dimensionality Reduction. Awaiting for a course on Recommender Systems and Deep Learning
by Ning A•
Sep 16, 2016
Learn more than just classification, but also learn how to understand the ideas behind classification algorithms.
by Yingnan X•
Apr 14, 2016
A good course to start learning classifications and getting exposure to algorithms. The instructor is awesome!!
by Oleg R•
Oct 09, 2016
I would prefer more complex assignments and more advanced math concepts in the course. Otherwise it is great.
Oct 12, 2016
Good course.. Should have SVM related info too -- waiting for the promised optional videos from Prof. Carlos
by Tomasz J•
Apr 04, 2016
Great course! However I put only 4 starts because I would like to see random forests which are not present.
by Baubak G•
Jun 10, 2018
I think the course on boosting could be worked on better. But all in all I really enjoyed this course.
by Srinivas C•
Dec 02, 2018
This course was really good and helped in understanding different techniques in Classification
Jul 20, 2018
The lecturer speaks in a quite unclear manner, besides, everything is great and detailed.
by Rattaphon H•
Aug 13, 2016
The questions are hard to understand and ambiguous though their answers are easy.
by Bruno G E•
Apr 17, 2016
Lack some of classical classification algorithms like SVM and Neural Netwroks.
by Jacob M L•
Jun 24, 2016
Very approachable material, given the diversity of classification algorithms.