I will present my self with some amazing songs!!

Excellent staircase to the heaven for learning PCA.

Breaking the habit of struggling with hardcore bookish mathematics.

Loose yourself in this adventure!!

Well explained, some issues with assignments but some of them are to not just type and think a little.

May be one is a real mistake... hard time with it, but lot of learning too.

Challenging, but doable. Has some bugs in coding assignments, but clearing them out makes you understand things better. Get ready to spend extra time understanding the concepts.

Very challenging course, requires intermediate knowledge of Python and the numpy library. PCA week 4 lab was truly a mind-blowing experience, taking over 5 hours to complete.

This course is well worth the time. I have a better understanding of one of the most foundational and biologically plausible machine learning algorithms used today! Love it.

Practices and quiz are designed well while I will suggest to put more hints on programming parts, e.g., PCA. Overall, this series of course are pretty useful for beginner.

This is the best course of the specialization, its very hard but it lets you to understand very important concepts of what means dimensionality reduccion.

Great Job!!!!

This course demystifies the Principal Components Analysis through practical implementation. It gives me solid foundations for learning further data science techniques.

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.

Really clear and well explained. The concepts are treated in detail enough to be applied. Very happy to have invested my time in this course. I strongly recomend it.

Definitely the most challenging of the course making up this specialization. Finishing it with full scores is proportionally far more satisfying!!! Well done Marc!

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.

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

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.

Great Course!

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

Although the course was little out there and the instructor was trying his best to articulate a difficult topic, the overall experience is great.

Nicely explained. Could be further improved by adding some noted or sources of derivation of some expressions, like references to matrix calculus

great content however the programming part is too challenging for people without propre guidance in the subject. the videos aren't of much help.

Solid conceptual explanations of PCA make this course stand out. The thorough review of this content is a must for any serious data researcher.

Just Brilliant!!! Very well structured with very clear assignments. Doing the assignments is a must if you want to get clarity on the subject.

This course should be part of "gems of coursera". Excellent specialization, thoroughly enjoyed it. For me the 3rd course on PCA was the best.

Excellent course. The fourth week material is the hardest for folks not comfortable with linear algebra and vectorization in numpy and scipy.

What a great opportunity this course offers to learn from the best in this simplified manner. Thank you Coursera and Imperial College London!

Excellent explanation from the professor!! Besides he is the author of the book Mathematics for Machine Learning. You should check it out.

Highly informative course! Loved the depth of the material. Found this course content highly useful in my current project based on PCA.