Learner Reviews & Feedback for Machine Learning Foundations: A Case Study Approach by University of Washington
About the Course
Top reviews
BL
Oct 16, 2016
Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much
SZ
Dec 19, 2016
Great course! Emily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.
2501 - 2525 of 3,156 Reviews for Machine Learning Foundations: A Case Study Approach
By Dorian K
•Mar 15, 2016
The course is great, you do learn a lot of the general concepts. I wish they would use general python packages instead of graphlab, but this is not a deal breaker.
By Owen M
•Feb 6, 2016
The course was taught well, however I thought there could have been a few more videos with more details. Although I understand that it's really an overview course.
By Fearghal O
•Feb 5, 2016
Really interesting course that gives a great introduction to Machine Learning. Might be a little too much for someone with no programming or statistics experience.
By pradyut n
•Jul 18, 2020
Libraries are old and no support . Though I somehow worked it out.
But man explanations are so good and the professors are nice too.I like how they make us laugh .
By Andrei N
•May 27, 2020
Really good introductory course. Sadly the code in the video is not up to date and there are points were the questions are quite vaguely formulated in the quizes.
By Vishakha V
•Apr 10, 2018
The course is great for beginners, I would have appreciated a more detailed explanation of statistical models used rather than using readymade graphlab functions.
By Sachin P K
•Mar 2, 2020
Good for the beginners to learn Machine Learning and Neural Networks in detail. This course also includes hands on sessions/ assignments which helps in learning.
By Parijat R
•Feb 27, 2018
Many basic ML concepts were touched upon - the assignments, especially in Parts 1-4 were very easy and required very little brainstorming :) - hence a star less.
By Vladimir G
•Oct 26, 2017
The course is very comprehensible, even for not so technical people. The materials are good and the lecturers are able to explain complex concepts to everyone.
By KESHAV M 1
•Jun 26, 2020
This course has provided a very good insight of what are the tools that are applied in machine learning and how fast they are from the already existing tools.
By Luis G A P
•Dec 3, 2018
Good introductory course, some videos require more than one time to review them and even doing external research on the topics to understand well the concepts
By Michael S
•Feb 15, 2017
The lectures are substantive, although they tend to be too short in duration. The python application component is very applicable to work-related situations.
By Briana S
•Sep 21, 2016
Excellent course, very charming professors, accessible even for people with limited math/coding backgrounds. Some course material needs to be updated, though.
By Shivani D
•Oct 16, 2020
The course was wonderful. Had a great time learning with doing hands-on on real-time data. But there could have been a more detailed algorithm's explanation.
By SIVASHANKAR S
•Jan 11, 2019
The fundamentals of coding and machine learning concepts are taught in such a way that even a person with no background in computer science can grasp easily.
By Chengneng J
•Dec 22, 2018
really interesting and helpful to fresh, however it's little bit easy for who have learned something about machine learning and the experiments are too easy.
By José D d O F
•Aug 6, 2017
Provides a good very basic but broad view of the subject. Lectures are really good, but lacks written material and programming assignments are way too basic.
By Roberto S
•Dec 27, 2016
Very interesting course as the start of something that will get more and more interesting. I am happy that I got this specialization and not only the course.
By Volodymyr L
•Feb 2, 2016
I found here all I need for first step in ML. Thank you. But Assignment you should make different. I mean varied tasks but not the same for each new attempt.
By Sahil
•Mar 9, 2022
Everything is perfect except the library used which is turicreate is not as per current industry requirements, instead Pandas and Scikit learn can be used
By vikash k
•Jan 30, 2022
Great course. Really loved the content. But would have been better if they would have released the last two courses. Basically a finishing touch is missing.
By Ayush G
•Feb 19, 2017
The course is a very good introduction to the specialization. It'd have been better if the course used an open source tool instead of a proprietary product.
By STEFANO C
•Jul 3, 2016
A different version of graphlab was used without I think being duly noted, some functions work differently in newer versions. For the rest it was very good.
By Amit H
•Jan 12, 2016
Effectively introduces to the basics of all different machine learning algorithms through case studies. The recommended tools are easy to use and understand
By Niklas F
•Feb 24, 2017
Really good overview and easy start into the machine learning community. Only point is, that they do not use the usual python packages for machine learning