Great course to develop some understanding and intuition about the basic concepts used in optimization. Last 2 weeks were a bit on a lower level of quality then the rest in my opinion but still great.
Excellent course. I completed this course with no prior knowledge of multivariate calculus and was successful nonetheless. It was challenging and extremely interesting, informative, and well designed.
By Donna D C•
Nice balance between rigor and developing intuition (again as in the previous linear algebra course in this series). I would’ve liked some “homework” reading about backpropagation for training the simple neural to prepare for the future courses. Also, more references for additional reading on least squares minimization techniques to tie more into the statistics underlying the techniques. I love the stuff, thank you!!
By Dan L•
The course accomplishes its goal of connecting concepts in calculus to machine learning, and is appropriately paced for students who have covered calculus in the past and are seeking a refresher or deeper understanding of its applications to real-world problems. For those who don't already have a certain minimum familiarity with the mathematics, however, the course will probably move at too fast a pace.
By Matt P•
Great class - very informative and eye opening - even with quite a bit of linear algebra background. Really liked the eigenvector and eigenvalue section - great descriptions. I wish the neural network discussion went on a bit further. I found some of the programming assignments' instructions a bit vague and confusing - what should have taken a few minutes ends up taking a half hour.
By Aneev D•
This course is great in the sheer efficiency with which it goes through the content required to prepare you for machine learning. It builds an intuition for what's going on, which is amazing. Some parts are confusing, and I recommend looking at Khan Academy for the lectures on Jacobians and steepest ascent, and 3Blue1Brown for feedforward neural networks.
By Wenyuan Z•
Well the course is generally good, the only problem is that David sometimes may just skip the process and lack more explanation when performing the calculation, it's easy to lose track of what he is calculating if not reviewing the video over and over again, but anyway, the whole class is worth recommendation, thank you for your teaching, professors
By Anton K•
It was exciting at some points. However, I left the course with the feeling that some subjects were not covered properly. The technical aspect of the course (e.g. video quality, visualizations, practice with python) were really great, lots of interesting and new teaching methods (at least for me). I wish this course was longer and more detailed.
By Mihai R F•
Very valuable training course from the insight/intuition point of view. This is more of an overview of the calculus for machine learning giving the student a good direction of what to study and where to start from. I think that actually mastering the subject will require extensive additional exercises from other sources
By Dmytro B•
Very helpful to review and get introduced to mathematical concepts behind machine learning. There is a fair bit of practical exercises as well. The only thing I am less happy about this cousre was a lack of additional suporting materials and references to other resources to help gain more knowledge on the subject.
By Gerard G I R•
I had no previous experience with multivariate calculus. This was a nice introduction to the topic, but in my opinion it does not allow me to say that "I know" multivariate calculus. Nevertheless, I think it is work taking as an introduction before going to more complete courses in multivariate calculus.
By Luis M V F•
I think Samuel Cooper is an amazing instructor. However, the last two weeks taught by David Dye were very difficult to follow. I think David should improve his explanations because I did not enjoy too much his course on linear algebra, and this course was great until he started with the last two weeks.
By Abhirup B•
exercise and programming assignments are good ....and i can grow a sound concepts after completeing them.lectures are also good ...but some lecatures are too quick and a little elaboratiion in some places would have been helpful(particularly those in the last couple of lectures)
By Kevin E•
Excellent course. It covers so much without making me feel overwhelmed. I would like to see more hands-on demonstration on linear and non-linear regression, but I was able to complete the quizzes and assignments. This without any previous multivariate calculus instruction.
By Divyang S•
Overall a good course to give us a better idea of what sort of math is used in ML. But I feel they went too fast in this course, so I personally lagged a bit in understanding certain crucial concepts. Also, it'd be much help if the instructors could mention reference books.
By Michelle W•
I would say this entire series is better advertised as a quick *review* of the pertinent concepts. Otherwise, someone with no background in the topics covered may struggle (unless they are particularly talented with quickly learning new mathematical concepts).
By Glendronach 3•
This felt like time well spent. A really good course which I should have taken before doing the Machine Learning Course by Andrew Ng. That would have made life easier.
Beware, the 'gradient of the learning curve' at any point during this course is steep.
Generally, it is a good course. Many new tools and fancy representation method, but for mathematical idea and explanation, it is just too simple. Maybe the biggest contribution to me is that It lets me know the Kahn Academy and 3b1b courses.
By Aditya J•
Could have explained in a way that the audience requires a slower and better and little more in-depth explanation. Some places felt a little rushed, so had to spend more time in forums and other resources to get more idea. Overall was great.
By Saikumar S•
Need a bit more clarity in terms of integrating the calculus in the last week sessions.
I agree they are very good but would be great if there is some more additional clarity. And also some project using the whole course would be helpful.
By Ankit C•
It gives you a good head-start to the math required in Machine learning. Some major concepts are touched just on the surface level but the mathematics involved in those concepts is explained quite well. Overall, it's good experience
By SUJITH V•
Very good course to start of with mutivariable calculus basics. Helps to refresh your memory if already familiar with concepts, additionally helps in getting fresher perspective because of geometrical intuition presented very well.
By Switt K•
Good details, great at building intuitions. Instructors are pleasant to listen to :)
As expected, it's enough to get you going in the right direction, that if you want to know more, you'd have enough knowledge to build on from.
By George K•
Lack of support from the staff. Some parts/lectures are not clearly explained (for example, constrained optimization) and some quiz questions are not directly related to the course content. Otherwise, it's a very good course.
By Jacqueline B•
up to week 5 , it was masterpiece.
week6 (although it should be the most important one) was a mess and disappointing.. as it was not explainable, i couldn't link what is happening with previous weeks.. require to be enhanced
By Izzan D•
The first 3 weeks is really good, the fourth week is okay but the last 2 weeks is kinda confusing. The explanation is quite clear but it is quite hard to grasp the intuition and relationship between each material.
By Peiyuan C•
Along with the advanced and popular technique, this course gives me impressive insight over how machine learning works. But it would be much better if the concept in linear algebra combines more with this course.