2020년 6월 14일
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 :)
2016년 10월 15일
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!
교육 기관: Nitin D•
2018년 12월 18일
Excellent lessons on this important topic Classification. I think all major areas were explained quite nicely, with proper examples.
교육 기관: Dongliang Z•
2018년 3월 22일
Excellent course! The teacher explained a lot of intuitions during the course. The optional part s are very interesting and helpful.
교육 기관: Ornella G•
2016년 10월 1일
I really enjoyed the topics presented and the fluid way to present them. It's a very well done summary of the classification models.
교육 기관: Siddharth S•
2018년 1월 8일
Excellent course and all the concepts have been explained very simply and with an element of fun.
Many thanks to Emily and Carlos...
교육 기관: Alvin B K•
2020년 9월 28일
This was a very great course. I got the confidence to use ML algorithms and concepts efficiently and also write my own algorithms.
교육 기관: Gaurav c•
2019년 5월 22일
Would have loved even more had Carlos explained his students gradient boosting as well. I liked the way of his taught in lectures.
교육 기관: Ankur P•
2018년 5월 29일
Loved the way our tutor (Carlos) explained the concepts to us. Things are getting clearer with each course in ML :) Many thanks :)
교육 기관: Renato R S•
2016년 8월 27일
All the basics - and much of the advanced stuff - is presented, in a coherent and inspired way. Thanks for crafting such a course.
교육 기관: Joseph F•
2018년 4월 5일
Good course with many assignment to design the algorithm with your own code. But I think this course last a little bit too long.
교육 기관: Tanachote R•
2020년 4월 25일
Thank you for sharing your knowledge to me. This course is very good and I really appreciate both of you (Carlos and Emily)
교육 기관: Reinhold L•
2019년 3월 21일
Very good course for classification in machine learning - top presentation documents - very well structured and practical
교육 기관: Pawan K S•
2016년 5월 15일
Nice course with appropriate amount of detail in it! Covers tough mathematical aspect for those who are interested in it.
교육 기관: Fabio P•
2016년 4월 18일
Very interesting topic with some advanced topics covered. It really shows how to use machine learning in the real world.
교육 기관: Matthew S•
2020년 5월 22일
Great! Not horribly wretchedly awful, but actually very good! (With this class I hope this is classified correctly!)
교육 기관: Vibhutesh K S•
2019년 5월 22일
It was a very detailed course. I wished, doing it much earlier in my research career. Great insights and Exercises.
교육 기관: Igor K•
2016년 3월 16일
very interesting and novice friendly, however some math (basic matrix calculus and derivatives) review worth doing
교육 기관: Etienne V•
2016년 11월 13일
Great course with very good material! I'd like to see assignments that leaves more coding tasks to the student.
교육 기관: Naman M•
2019년 7월 9일
you can't find a better course on machine learning as compared to this one. Simply the best course on coursera
교육 기관: Divyang S•
2020년 9월 13일
Excellent and very in-depth coverage of basic and advanced concepts... Perhaps the best course out there !!!!
교육 기관: Emil K•
2020년 1월 29일
Such a great course. Brings the math behind machine learning to users without a math background. Thank you.
교육 기관: Naimisha S•
2018년 7월 30일
Availability of the Ipython notebook makes it easy to solve the Quizzes which has step by step explaination
교육 기관: hamed a•
2022년 7월 26일
Best machine learning course I have had so far! (guess this includes great words for a fantastic review)
교육 기관: Konstantinos P•
2017년 3월 28일
The context and the structure of the course is absolutely perfect. Also, Carlos is the perfect professor!
교육 기관: Hristo V•
2016년 12월 1일
The course is absolutely amazing! Very clear explanation of the concepts with great notebook assignments.
교육 기관: Shaowei P•
2016년 3월 31일
great course, would have been even more great if there are more details on how to use boosting for kaggle