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Mathematics for Machine Learning: Multivariate Calculus に戻る

インペリアル・カレッジ・ロンドン(Imperial College London) による Mathematics for Machine Learning: Multivariate Calculus の受講者のレビューおよびフィードバック



This course offers a brief introduction to the multivariate calculus required to build many common machine learning techniques. We start at the very beginning with a refresher on the “rise over run” formulation of a slope, before converting this to the formal definition of the gradient of a function. We then start to build up a set of tools for making calculus easier and faster. Next, we learn how to calculate vectors that point up hill on multidimensional surfaces and even put this into action using an interactive game. We take a look at how we can use calculus to build approximations to functions, as well as helping us to quantify how accurate we should expect those approximations to be. We also spend some time talking about where calculus comes up in the training of neural networks, before finally showing you how it is applied in linear regression models. This course is intended to offer an intuitive understanding of calculus, as well as the language necessary to look concepts up yourselves when you get stuck. Hopefully, without going into too much detail, you’ll still come away with the confidence to dive into some more focused machine learning courses in future....



Very Well Explained. Good content and great explanation of content. Complex topics are also covered in very easy way. Very Helpful for learning much more complex topics for Machine Learning in future.


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.


Mathematics for Machine Learning: Multivariate Calculus: 726 - 750 / 758 レビュー

by kumar s


Overall average course. Not that much good as expected because of David Dye. He was teaching very poor in this course as compared to course-1.

by TirupathiRao p


Last 2 weeks completely diverged. Failed to converge. I wish content was more elaborate.First course of this specialization was far better.



Role of discussion forum is very less. Please improve on that to have healthy participation. Otherwise, course content is really good.

by Kamol N


first 4 weeks were good. Starting from week 5 course explanation was bad. Was required to watch other videos.

by Lieu Z H


Lecture videos are quite sparse, and the quizzes test things that they don't teach you in the lecture

by Saurabh M


A bit fast paced, could be much more beneficial with some added explanations.

by Lee j


Too fast to understand what instructors says.. but lecture contents are good

by Akeel A


It was a lot of fun at points. Would recommend to anyone else.

by Gurrapu N


Strong disconnect between teaching videos and assignments.

by joseph k


Course would enhanced if pdf's of lectures were provided.

by Alkis G


There is a decent space for course improvement.

by prudhvi


week 6 content is not clear at least for me .

by สิทธิพร แ


Week 5 and 6 Lecture quite poor

by Leigh F


Concepts not clearly explained.

by Aviv P


many topic were explained badly

by Vivek P D


Explanation is not in depth

by Mahmoud T


Dr.Sam Cooper is the best.

by Abdelftah M


Change the bald man.

by Rishabh J


Not very challenging

by Reena J


contents Are Useful

by Tianchi M (



by chanhee


It's nice

by Alexander M



by Alois H


The material is great and very relevant to anything connected to data science, however, I didn't enjoy this course half as much as the first in the series.

It's way too dense, things appearing on the screen where it's not clear where they're coming from, explanations feel scripted and read out at high speed, frequently unclear.

If you're using screen shots for taking notes (as I do), that's not ideal either because they're writing on a glass pane while they're standing behind it.

I'm working full-time and had to take this course stretched out over a long time. Again, the presentation being so dense doesn't help there either.

All in all it feels like a published first draft of the course, it doesn't seem the instructors are trying to improve the course at all.

by Paul K M


I am not sure if this course is for people who know calc, and want to learn python coding or people who know coding and want to learn some calc? Frankly it isn't a great course for either group. I knew some calc, and some python going in, and I did expand my knowledge and gain some useful practice. But it left me craving rigor.