Now i feel confident about pursuing machine learning courses in the future as I have learned most of the mathematics which will be helpful in building the base for machine learning, data science.
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.
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 Prut S•
The content was challenging but very well structured. It is nice to understand the mathematics behind it rather than just blindly using PCA in your projects.
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 Bui V H D•
I think it is the best hard in 3 course of the series, but It give many new knowlegde and build a mindset with math for machine learning.
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 qwer q•
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 Amar n•
Just Brilliant!!! Very well structured with very clear assignments. Doing the assignments is a must if you want to get clarity on the subject.
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.
I liked how practical this course was. The programming assignments were really beneficial for a deeper understanding of the material.
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 Giorgio B•
The leadup to PCA was needed and thought clear. I now have a better understand of how projections and inner products work.
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 Teiichi A•
Challenging, with a lot to fill between the topics. Was shown how much further I can learn, which I am really grateful.
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!