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.
May 01, 2018
This course was definitely a bit more complex, not so much in assignments but in the core concepts handled, than the others in the specialisation. Overall, it was fun to do this course!
May 29, 2019
This was indeed a very challenging course. It was also very rewarding, and I felt that the instruction was great and relevant to the assigned tasks. The first two courses in the specialization were very high quality, and in my opinion this one lives up to the expectations that they set.
By FRANCK R S•
Jul 07, 2018
Very interesting and challenging subject: PSA, this MOOC together with the other 2 Mathematics for Machine Learning are one of the most useful I have ever made, actually they helped a lot in my other Machine learning and Deep learning studies! I highly recommend this fascinating MOOC
By mohit t•
May 13, 2018
Perfect course. It takes up more time and effort than the other two courses in the specialization. But what you learn by the end of it is totally worth the effort. Note that this is an Intermediate course compared to the other two which are beginner. So the extra rigor is expected.
By Oj S•
Jan 13, 2020
The introduction to PCA and steepest descent algorithms which might be a century old but still act the fundamentals of many state of art equations. So, you will learn the basics that how they function, and the real mathematics you need to know for ML using this course.
By Anna U•
Jan 14, 2020
An excellently simple explanation of concepts of linear algebra and PCA. Applause for lector. I really liked this course and found it very useful for those newbies in machine learning like myself. I recommend this course to all my friends and others interested in.
By Ramon M T•
Oct 23, 2019
I liked the course quite a bit. I found it quite challenging (I had never seen any PCA) but it always kept me very interested. I had to use several sources to read a little more about PCA and to complete the last exercises, the forum is very helpful.
By Xavier B S•
Apr 05, 2018
Excellent course - challenging yet rewarding with good feedback from the teaching staff.
The video and the transparent white board are also great - look forward to seeing more MOOCs from Imperial as well as the release of the upcoming book
By Jafed E•
Jul 06, 2019
I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand
Jul 18, 2018
This one is harder, I took longer time to figure out the assignments. Some of the concept that appeared in the assignments were not included in the lectures. I do hope that the assignments could have clearer instructions.
By Abhishek M•
Jun 22, 2019
Very nice course. It will be great to have a course on Statistics for Machine learning covering advanced concepts in probability theory. Thank you for offering such a great course. I have learnt a lot and enjoyed fully.
By María J S G•
Aug 29, 2019
Very good 3 courses for those of us who are beginners in Machine Learning and IA! However I miss a whole course, perhaps the first one of then four, teaching us what we need to know about python, numpy and plotting.
By Arnab M•
Jun 03, 2019
A great course. Learnt a lot, a lot of Linear Algebra, Projections/ Geometry/ all of these Mathematical ideas would help greatly in understanding of Machine Learning concepts and applying them to real world data!!..
By Krishna K M•
Jun 24, 2019
I am not sure why the rating is so low for this course.
Personally, I found this course really insightful as the instructor explains what the different statistical measurements mean, and why are they useful.
By Akshat S•
Jul 24, 2019
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!!
By Aleksey A•
Feb 15, 2020
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.
By Christian H•
Dec 28, 2019
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.
Mar 14, 2018
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.
By Aymeric N•
Nov 25, 2018
This course demystifies the Principal Components Analysis through practical implementation. It gives me solid foundations for learning further data science techniques.
By Christine D•
Apr 14, 2018
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 Prime S•
Jun 24, 2018
Nicely explained. Could be further improved by adding some noted or sources of derivation of some expressions, like references to matrix calculus
By J A M•
Mar 21, 2019
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 Moez B•
Nov 25, 2019
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•
Dec 31, 2018
What a great opportunity this course offers to learn from the best in this simplified manner. Thank you Coursera and Imperial College London!
By Alexander H•
Jul 31, 2018
Highly informative course! Loved the depth of the material. Found this course content highly useful in my current project based on PCA.
By Dora J•
Feb 04, 2019
Great course including many useful refreshers on foundational concepts like inner products, projections, Lagrangian etc.