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!
創建者 Vassiliy T•
Jul 10, 2018
it is good, challenging course. i've learned a lot, but feel that i came away with quite patchy knowledge. This course is a big step up in complexity and delivery form the previous two courses. perhaps my expectations were not right to start with - one cannot learn this level of complexity so quickly. Admittedly there are many gaps between the lectures and course materials and what is asked in programming assignments. i ended up reading a lot online to fill in the gaps (i've learned a lot of python during the course, which is great!).nevertheless, after this course i feel equipped to continue with machine learning.
創建者 Nikolay B•
Aug 03, 2019
Instructor gives the very dry but useful essence of the "philosophical" concepts of dot and generalized inner product, etc., - personally, liked that. Unfortunately, the offered problems are so far away from the delivered videos but the web search helps on getting the hints. This course makes you think - I learned a lot just by asking myself "what do they mean under this statement?", what they want in this task? Though I will appreciate if providers elaborate the material further and so instead of googling we spend our time watching - a single point access.
創建者 Barnaby D•
Jan 03, 2020
Would give this course 5 stars if it was properly described so that expectation could match reality:
Give yourself plenty of time for this course - it will take quite a bit longer than described.
Make sure you are comfortable with Python and NumPy before you start (particularly the linear algebra functions).
It is very different (much less hand-holding) than the other courses in the specialization.
創建者 Nelson F A•
Apr 25, 2019
This course brings together many of the concepts from the first two courses of the specialization. If you worked through them already, then this course is a must. There are some issues with the programming assignments and the lectures could do with some more practical examples. Be sure to check the discussions forums for help. For me they were essential to passing the course.
創建者 Evgeny ( C•
Jul 25, 2018
It was a harder course where I spent double the time I have initially anticipated.
It is much harder than the two predecessor courses in specialization, and amount of direction when it comes to doing exercises is significantly smaller. More Python knowledge is required.
That said, I feel like I have finally understood the PCA and math behind it, which made it all worth it
創建者 Mark S•
Jul 07, 2018
Loved the course, although I wish there was more ramp up to some of the complex scenarios (or anything simple but new). Very helpful forums/community. Requires a fair amount of external reading/referencing for some of the concepts which seem to be covered only at a high level in the lectures.I would love to see more courses on applied mathematics for machine learning.
創建者 Jerome M•
Jul 26, 2018
The best of the 3 courses. This is a refresh course of course. A solid background in linear algebra is required in order to fully understand everything. I personnaly recommen the MIT course from Gilbert Strang before you try this one. The python exercises are very well designed and I can only be thankful to having shared this knowledge. Thank you Imperial College.
創建者 Timo K•
Apr 10, 2018
Not quite as good as the other two courses of the same specialization. Even though the instructor seems immensely knowledgeable he could work on delivering the material (which is more abstract than before to his credit) in a clearer manner.
The programming assignments are great albeit a bit hard to troubleshoot at times. All in all still a great course.
創建者 Joshua C B A•
Mar 11, 2019
Very good course. I liked every single video and exercise. I feel that the programming assignments were a bit more challenging and sometimes I was not too sure of what I was doing. I am not a professional in handling Python, so I had to surf online finding the commands to be able to build the simplest code possible. Other than that, it was enjoyable.
創建者 Cheng T Y•
Jul 08, 2018
good thing is it's trying to give you a sense of practically how to do it.downside is it's not really bridging to from maths to that practical sense in python (and the online jupyter notebook is terrible).the teaching staff is actually more responsive than the other 2 in the specialization.a bit more sided on python than maths though.
創建者 Phạm N M H•
Jul 12, 2019
This maybe the most frustrating course and most advance compare to 2 other courses, you might confuse about the code in the assignment of this course. So, if you do have basic background about coding with numpy, matrices,etc..., I do recommend this course, if you qualify enough to fix the bugs of what the dev team left.
創建者 Thorben S•
Mar 08, 2019
I would have liked to be introduced to the topic on a higher level first - and then, step by step, an introduction of the math to solve specific problems in the progress. That would be a perfect approach, especially for data scientists who just want to understand the underlying math for such a widely used technique.
創建者 Shariq A•
Oct 20, 2019
Thank you professor for providing such a valuable course.
Just I wanted to say one thing without hurting anyone, the week 4 on PCA is not very clear. The derivation are not very correlated .A humble request isthat to elaborate the derivation which would further enhance the learning
創建者 Jonathan F•
Mar 17, 2019
This course is way harder than the first two. The maths itself is more difficult. The Python parts are a lot more challenging because they require a good understanding of the way Numpy handles vectors and matrices. But the end result is good and it is worthwhile!
創建者 Gaetano F•
Oct 10, 2019
I found the course excellent but in the programming assignments is not always clear what should one exactly do. They are also quite confusing, especially the last one on PCA implementation. One wastes so much time trying to figure out the solution.
創建者 Ronald T B•
Jan 21, 2019
it is very challenging course, of course you will complain at first on how lack the programming explanation is given. However, it just like the ingredients the math for machine learning will not be complete without attempting to this one.
創建者 Вернер А И•
Mar 18, 2018
Very tough course because of the programming assignments. Material was sometimes taught in a non-clear and deceiving way, e.g. covariance matrix of a dataset. Nevertheless, the course is good and covers lots of important details.
創建者 SUJITH V•
Sep 28, 2018
This is a great course. It covers the topic in good amount of detail. I have enjoyed this course a lot and it also made me think deeper at a lot of places. I am motivated to go and do more work on related topics now.
創建者 João M G•
Aug 14, 2019
The course was great till the final week. The lectures did not explain very well the concepts and the assignment was poorly designed. It's a shame because I've loved the more rigorous way of this final course.
Aug 29, 2019
I think it's really a hard lesson for me, but I've also learn a lot, thanks a lot for the teacher and coursera. Some Programming test take too long to execute, and there are some errors in it. just be careful
創建者 Suyog P•
Sep 02, 2019
Finally understood basic intuition of PCA, never got perfect resource before. However, there was a sharp change in terms of course delivery than the previous two courses of this specialization. So, heads up.
創建者 Camilo J•
Mar 01, 2019
Great capstone for the three-class Mathematics for Machine Learning series. Assignments were way harder and programming debugging skills had to be appropiate in order to finish the class.
創建者 Abhishek P•
Sep 09, 2019
Course content tackles a difficult topic well. Only flaw is that programming assignments are poorly designed in some places and are quite difficult to pick up at times.
創建者 Liang S•
Jul 09, 2018
Teaching pacing is good, and clear in explanation. It will be good if there are some examples about how we should apply all these theories to some real problems.
創建者 Mohamed B•
Oct 27, 2019
I learned a lot in this course, though the last week was somehow hurried and the lecturer didn't spend enough time to piece the whole stuff together.