Jul 17, 2018
This is one hell of an inspiring course that demystified the difficult concepts and math behind PCA. Excellent instructors in imparting the these knowledge with easy-to-understand illustrations.
Jun 19, 2020
Relatively tougher than previous two courses in the specialization. I'd suggest giving more time and being patient in pursuit of completing this course and understanding the concepts involved.
Aug 29, 2019
I think it's really a hard lesson for me, but I've also learn a lot, thanks a lot for the teacher and coursera. Some Programming test take too long to execute, and there are some errors in it. just be careful
创建者 Suyog P•
Sep 02, 2019
Finally understood basic intuition of PCA, never got perfect resource before. However, there was a sharp change in terms of course delivery than the previous two courses of this specialization. So, heads up.
创建者 Camilo J•
Mar 01, 2019
Great capstone for the three-class Mathematics for Machine Learning series. Assignments were way harder and programming debugging skills had to be appropiate in order to finish the class.
创建者 Lotachukwu I•
Jun 28, 2020
Very challenging at times, but very good course none the less. Would recommend to any one who has a solid foundation of Linear Algebra (Course 1) and Multivariate Calculus (Course 2).
May 28, 2020
Course content is interesting and well planned, Can be improved by making it Simpler for Students as it was more technical than the other 2 courses of the Specialization.
创建者 Abhishek P•
Sep 09, 2019
Course content tackles a difficult topic well. Only flaw is that programming assignments are poorly designed in some places and are quite difficult to pick up at times.
创建者 Hadhrami A G•
Jun 08, 2020
The course is generally good but the assignment setting definitely needs to be rectified. Thanks anyway for this course. An important element of machine learning.
创建者 Liang S•
Jul 09, 2018
Teaching pacing is good, and clear in explanation. It will be good if there are some examples about how we should apply all these theories to some real problems.
创建者 Mohamed B•
Oct 27, 2019
I learned a lot in this course, though the last week was somehow hurried and the lecturer didn't spend enough time to piece the whole stuff together.
创建者 Rok Z•
Feb 05, 2020
A different course than the previous 2.
Much harder - as you have to actually know some Python tricks.
But I guess it's the same in a real world.
创建者 Jordan V•
Aug 23, 2019
Course addresses important subject, but I worth like to have more in-depth explanation of the mathematics by the instructors and more examples.
创建者 Kevin G•
Jan 14, 2020
Felt like explanations in this course were a bit confusing, but otherwise, it was a very interesting course. Thank you so much for doing this.
创建者 Helena S•
Feb 28, 2020
The final Notebook contains some errors (Xbar instead of X, passed as an argument). Otherwise a very well organized course. Thanks a lot!
创建者 Giri G•
Jun 07, 2019
This was a very hard course for me. But I think the instructor has done the best possible he can with presenting and explaining the course
创建者 Leon T•
Jul 10, 2020
Jupyter notebook assignments are in desperate need of attention! Very buggy or non-intuitive for the scope of material in span of time.
创建者 Christine W•
Aug 13, 2018
Coding assignment is hard for people who are not familiar with numpy. Would appreciate some material at least going over the basis.
创建者 Shaiman S•
Apr 30, 2020
Please change courese material for PCA. It is very un-understandable and assignments are also very tugh as per what is taught.
创建者 Karan S•
Aug 01, 2020
Focus a bit more on PCA in week 4, week 1 was not very informative and should be assumed as required knowledge for the course
创建者 Hilmi E•
Apr 20, 2020
Careful, step-by-step construction of the PCA algorithm with practical exercises and coding assignments.. Very well done...
创建者 Voravich C•
Oct 21, 2019
The course level is very difficult and I think having four week course is not enough to understand the math behind PCA
创建者 Nguyen D P•
Oct 17, 2018
That's a great online courses can help people have enough background to break into Machine Learning or Data science
创建者 Ananthesh J S•
Jun 16, 2018
The PCA derivation part requires more elaborate explanation so that we can understand the concept more intuitively.
创建者 Manuel I•
Jul 07, 2018
Overall the hardest of the specialization, a though one but great to make sense of all the maths learned so far.
创建者 Shraavan S•
Mar 04, 2019
Programming assignments are a little difficult. Background knowledge of Python is recommended for this course.
创建者 Andrew D•
Jun 02, 2019
Very difficult course, make sure to do the prereq courses first and understand everything from those courses.