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 Manuel G•
Jan 01, 2019
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.
By Theodore G•
Oct 21, 2016
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.
By B M K•
Oct 16, 2016
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.
By Nitish V•
Jul 06, 2017
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.
By Ahmed N A•
May 04, 2018
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.
By David E•
Aug 21, 2016
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.
By Wenxin X•
Mar 26, 2016
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!
By Maria C•
Mar 08, 2016
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.
By Marcio R•
Jun 14, 2016
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.
By A S P•
Nov 14, 2016
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.
By Ian F•
Jul 18, 2017
Good overview of classification. The python was easier in this section than previous sections (although maybe I'm just better at it by this point.) The topics were still as informative though!
By Jason M C•
Mar 29, 2016
This continues UWash's outstanding Machine Learning series of classes, and is equally as impressive, if not moreso, then the Regression class it follows. I'm super-excited for the next class!
By M L•
Mar 14, 2016
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.
By sudheer n•
Jun 12, 2019
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
By Prajna P•
Dec 18, 2017
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
By Jenny H•
Jan 01, 2017
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!
By Joshua A•
Sep 20, 2016
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!
By Renato V•
Jul 13, 2016
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.
By Thomas E•
May 12, 2016
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 :)
By Shaik R•
Jul 12, 2019
Best Machine Learning classification course by far....
each aspect is explained in detail..but forum responses can be improved..
Great course for machine Learning beginners... loved it.
By Krisda L•
Jun 24, 2017
Great course. I learned a lot about Classification theories as well as practical issues. The assignments are very informative providing complimentary understanding to the lectures.
By Michele P•
Aug 23, 2017
The course starts slow, but it gets more interesting from week 2. The assignments are more challenging than in Regression, but I have really enjoyed it. I highly recommend it!
By Dhritiman S•
Feb 09, 2017
These courses have been a perfect mix of theory and practice. Looking forward to the final two courses in the specialization getting released at some point in the future :)
By Phil B•
Feb 13, 2018
Excellent overview of the most commonly used Classification techniques, providing the wireframe for us to write our own algorithms from scratch. Really enjoyed this one.
By Kuntal G•
Nov 03, 2016
Great course with detail explanation ,hands-on lab along with some advance topic. Really a great course for anyone interested in the field of real world machine learning