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.
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.
By XL T•
It is a bit difficult and jumpy. You will need some hard work to fill in the missing links of knowledge which not explicite on the lectrue. Overall, great experience.
By Fabrizio B•
Definitely the most challenging of the course making up this specialization. Finishing it with full scores is proportionally far more satisfying!!! Well done Marc!
By S J•
Your Teaching and Video quality is par excellence.....Thanks a lot for such amazing stuff...I am looking forward to joining more courses in the same line
By Christine D•
I found this course really excellent. Very clear explanations with very hepful illustrations.
I was looking for course on PCA, thank you for this one
By Ananta M•
Although the course was little out there and the instructor was trying his best to articulate a difficult topic, the overall experience is great.
By Prime S•
Nicely explained. Could be further improved by adding some noted or sources of derivation of some expressions, like references to matrix calculus
By xiaoou w•
great content however the programming part is too challenging for people without propre guidance in the subject. the videos aren't of much help.
By J A M•
Solid conceptual explanations of PCA make this course stand out. The thorough review of this content is a must for any serious data researcher.
By Sateesh K•
This course should be part of "gems of coursera". Excellent specialization, thoroughly enjoyed it. For me the 3rd course on PCA was the best.
By Moez B•
Excellent course. The fourth week material is the hardest for folks not comfortable with linear algebra and vectorization in numpy and scipy.
By Hasan A•
What a great opportunity this course offers to learn from the best in this simplified manner. Thank you Coursera and Imperial College London!
By Duy P•
Excellent explanation from the professor!! Besides he is the author of the book Mathematics for Machine Learning. You should check it out.
By Alexander H•
Highly informative course! Loved the depth of the material. Found this course content highly useful in my current project based on PCA.
By Prabal G•
great course for mathematics and machine learning...A big thanks to my faculty to guide like a god in this applied mathematics course
By Jason N•
A lot of reading beyond the video lectures was required for me and some explanations could be more clear. Overall, a great course.
By Rishabh P•
Well-detailed course and straight to the point. I enjoyed the course even though the programming assignments can be challenging
By UMAR T•
Excellent course it helps you understanding about linear algebra programming into real world examples by programming in python.
By Josef N•
It would be great if the course is extended to 8 weeks, with the current week 4 spanning at least 3 weeks. Otherwise great.
By Dora J•
Great course including many useful refreshers on foundational concepts like inner products, projections, Lagrangian etc.
By Trung T V•
This course is very helpful for me to understand Math for ML. Thank you Professors at Imperial College London so much!
By Mukund M•
Professor Deisenroth is amazing. Very tough course but appreciated all the derivations and explanations of concepts.
By David H•
It was challenging but worth it to enhance the mathematic skills for machine learning. Thanks for the awesome course.
By Lee F•
This was the toughest of the three modules. It gave me a strong foundation to continue pusrsuing machine learning.
By Nileshkumar R P•
This course was tough but awesome. Lots of things i learnt from this course. Great course indeed and worth doing.
By Nishek S•
The PCA part Was a bit tricky barely handle the concepts.
thank you imperial team for such interactive course