Learner Reviews & Feedback for Mathematics for Machine Learning: PCA by Imperial College London
About the Course
Top reviews
JS
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.
NS
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.
351 - 375 of 451 Reviews for Mathematics for Machine Learning: PCA
By Ana P A
•Apr 22, 2019
The professor of other two a way better. This one skips some steps in some explanation that makes the tasks hard to do
By Chuwei L
•Apr 05, 2019
worse than previous courses of machine learning specialization. Really confused me when introduced the inner products.
By Jyh1003040
•Jul 09, 2018
Honestly this course is the one worthing attempting. However, last week's content is really messy and challenging.
By Hsueh-han W
•Sep 20, 2019
many steps are not clear enough that I have to spend a lot of additional time to figure out the details.
By Gurudu S R
•Sep 16, 2019
Tutor is not clear and concise on the concepts. Need more examples for Week 2 and Week 3.
By Vishesh K
•Mar 13, 2020
Good Content but isnt't explained well. if you are motivated by yourself then go for it.
By Sagun P S
•Mar 14, 2019
Tough one if you are new to programming or doesn't have excellent understanding of Maths
By Keng C C
•May 30, 2020
explanations are not clear, need to refer to lots of youtube to catch up with course.
By Matan A
•Oct 20, 2019
The is a lot of gap from what the lecturer learn and what the assignments requires.
By Yuxuan W
•Oct 05, 2018
Always spending much more time on coding than needed. Same result but no credit :(
By Rafael C
•Dec 07, 2019
definitely one of the most catastrophic courses I've ever taken on Coursera...
By Meraldo A
•May 08, 2018
The course content was good; however, it was not well explained at times.
By connie
•Mar 21, 2020
I think content of first 2 weeks are disconnect with 3rd and 4th weeks
By Alexander
•Nov 06, 2019
Math for the sake of math. Too big jumps in calculations, too complex.
By k v k
•Nov 30, 2018
its a good course to learn mathematics essential for machine learning
By Rafael C
•Sep 24, 2019
The Classes didn't give the knowledge to solve the assignments.
By Shuyu Z
•Oct 18, 2019
The videos and instructions for the assignment are not clear.
By gaurav k
•Jul 03, 2019
More examples and visualization should be there to explain.
By Malcolm M
•Mar 06, 2019
Far more challenging than the first two courses.
By A. S M S H
•Jun 02, 2020
Theories should be explained more detailed.
By Reinaldo L N
•Feb 27, 2020
Last assignment was hell on Earth...
By Kirellos M H
•Apr 08, 2020
This course needs more examples.
By Sean W
•Nov 25, 2019
Notebook extremely buggy
By Felipe M
•Jul 26, 2020
It is a shame that this course isn't taught in a favorable way, as the content it has is very interesting and valuable. I found that the instructor lacked the enthusiasm that David Dye and Sam Cooper had in the previous courses, which obviously doesn't change the content of the course but definitely makes the learning experience worse. The lectures were also quite fast-paced and not very clear, I feel that this course should have been longer as when it was time to do the graded assignments, I had very little intuitive understanding of the concepts learned. The programming assignments were also the worse of the three courses; this is a combination of what I believe to be an issue with Coursera's online programming environment and the assignments themselves. The assignments were poorly explained and usually involved skills that were not even presented in lectures, which meant that unfortunately I had to rely heavily on books from the internet and assistance from fellow peers in the forums. Apart from requiring skills that were not taught, the Jupyter Notebook was unorganized in the sense that I felt unclear about where I should edit, where I should not. The programming assignments with the previous courses in this specialization were done in a much better way, guiding us to the solution while still demanding creativity and insight into the concepts, while the ones in PCA were messy. This is really sad as this is the most programming-heavy course. Overall I am quite disappointed with this course, it is a frustrating way to end this specialization with the two amazing previous courses.
By Pedro L
•Apr 26, 2020
Having taken the other two courses for this specialization, a certain standard was defined and expected. The other two courses had solid basis explained by the professors, and the assignments reflected well from the lessons showing a lineal progression to adequate difficulty.
In this course unfortunately it is not the case, the maths and basis are explained well enough, with extra lectures and side investigations needed from the user side in order to fully understand each lecture, and then the assignments. Don't expect immediate response form mentors nor teaching staff, and neither a well thought difficulty progression. The assignments done by hand and examples taught during lectures DO NOT reflect the difficulty level on programming assignments because it is expected you already have previous experience with python (which is rather frustrating as I took this course expecting to be entry level only on this language).
TL;DR: Take the first two courses if you wanna strengthen your basis, but the last course is not recommended
