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!
par Mark C•
Jul 31, 2018
Only on week 1 but this is already a disappointment compared to the first two classes in the Math for ML series which were excellent. Some content is presented too fast. Quiz questions are ambiguous. I already paid for the class so I will finish the content but not worry about passing quizzes and assignments. Had I known it would be like this I wouldn't have paid for it. Check out the other reviews and forum discussions to see what others think.
par Xiao L•
Jun 03, 2019
very wired assignment, a lot of error in template code. The concept is not clear.
par Tobias T•
Jul 14, 2019
If you like traditional lectures, which you go into a math class then feel puzzled, then go for it. Otherwise, the contents of this course are simply going through the mathematics equations and definitions, which can easily be found in textbooks. Ironically, the previous two courses in this specialization used lots of graphics and animations to help you understand the maths (either in terms of equation-wise or intuitively), this course completely lacks this element.
par Michael D•
Jul 22, 2019
After having done the first two parts of the specialization, I am afraid this one didn't stand up to the high quality bar the previous two had set. The programming assignments are unnecessarily long and complex and the overall material is not as engaging, connected and concise. I might give it a good rating as a standalone but now I can't avoid comparing it to the other two parts of the specialization.
par Max B•
Aug 14, 2019
Pretty bad all around.
The teacher keeps throwing formulas without taking the time to explain why they are useful, and what they represent.
The first two courses were really good, and this one is a bummer.
Most of what I learned was learned elsewhere, the course acted as a detailed syllabus with some practice quiz (of relatively poor quality).
It's still worth taking if you completed the first two courses and want the specialization certification.
par Aravindan B•
Sep 24, 2019
Need to improve the content and delivery of content.
Jun 08, 2018
This course is far far far behind my expectations.The other two course in the specializition is fantastic. There is no visualization in this course, Instructor is always doing his algebra, concepts are poorly explained. I can't understand a lot of concepts in this course because of my poor math background.But why do i take ths course if i have a solid background in math? Programming assignments is not difficult but hard to complete because of vaguely clarification.Plenty of time wasted to find what should i do, its' really frustrating.
par Nithin K•
Jun 05, 2018
Too conceptual and theoretical making it difficult to understand. Examples would have helped a lot.
par Kannan S•
Apr 11, 2018
There are no numerical examples as the course progresses. The instructor does everything algebraically. As a result I was not able appreciate the practical use of PCA. Later on I saw there are very nice videos in Youtube that illustrate the concept more lucidly using numerical examples. I am disappointed.
par Cynthia M•
Jun 09, 2018
The course is mathematics for Machine Learning. Yet, they require that you are proficient in python. I understand the mathematics. However, no one will answer my questions on the python we are suppose to code. I passed both of the previous courses. I've taken and passed Statistics with python on edX. I've very disappointed in this course.
par Matt C•
Jul 01, 2018
I was expecting to learn a lot in this course. I did not. The lectures don't really explain much at all and then you're thrown a quizzes and assignments that do not match what was in the actual lectures. The rest of the specialization was great but this course falls of the other two.The explanations in the videos are very poor. Really disappointed.
par Jared E•
Aug 25, 2018
Impossible to do without apparently an indepth knowledge of python.
par Kristina S•
Aug 24, 2018
One of the worst online courses I have had. Inconsistent teaching, relaying on students having previous knowledge about Python and rads (where the heck did that come from?), failing to convey what and where this is practically used for.
Aug 19, 2018
By far the worst online course that I've ever done. Assignments require a lot of experience in Python, which is not communicated upfront. At the same time, staff doesn't provide any actual support.
par Vibhutesh K S•
May 18, 2019
This course is really bad and extremely hard to follow. Previous two courses were executed very well, teaching quality in this is poor.
par Horacio G D•
Jul 31, 2019
Feedback for the assignments sucks! The discussion forums don't help. I have to submit the last assignment last 6 times until it work, and I still don't know why my previous versions didn't pass. Other than that, the lectures are actually very good, but the only one worth the time is the fourth one, the other three are just the first course (Linear Algebra) all over again.
par Anofriev A•
Oct 01, 2019
The worst course ever
par Danielius K•
Sep 24, 2019
You will spend most of your time lost.
Quizes are not clear and ill-prepared.
You will need to spend a lot of time looking for material outside of the course to actually make progress.
par Yan Z•
Oct 13, 2019
Marc Peter Deisenroth jumps too much at the important computation steps. Some steps might be simple to him, but it could be very misleading to students.
Often times, he will just throw out some equations without letting the student know what exactly we are trying to achieve.
par Wang Z•
Oct 20, 2019
Poorly organized and extremely confusing