# 学生对 伦敦帝国学院 提供的 Mathematics for Machine Learning: Multivariate Calculus 的评价和反馈

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3,571 个评分
615 条评论

## 课程概述

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....

## 热门审阅

##### JT

Nov 13, 2018

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.

##### SS

Aug 04, 2019

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.

## 51 - Mathematics for Machine Learning: Multivariate Calculus 的 75 个评论（共 619 个）

May 27, 2020

A great course. Engaging videos, understandable and solvable quizzes and assignments, and enthusiastic instructors. Gained a lot of insight into the topic, and this is coming from a person who has done Multivariate Calculus in University. Loved the part on Taylor's theorem.

May 31, 2020

This is an excellent refresher course on differential calculus emphasizing applications to machine learning. Exercises and quizzes are a mixture of solving problems by hand and completing Python coding challenges. I found this course to be very effective and worthwhile.

Mar 26, 2020

Multivariate Calculus - part of Math for machine learning is a good course to brush up your math skills or to learn the basics of Calculus behind ML. Its a introductory course that helps to understand Taylor series, Jacobians , Hessians. OverAll this is a good time spent

Aug 25, 2019

All the mathematical constructs and deep calculus was explained in a very intuitively with the help of visually rich animations. It seems the course content creators have spent good amount of effort in creating animations for every little useful thing, kudos to them.

Feb 19, 2019

I began this course without any knowledge of calculus and I was still able to get along decently well. I did a bit of supplementary work using Khan Academy but that was more to ingrain the calculus knowledge gained (product rule, chain rule, etc) within this course .

May 28, 2020

Very Intuitive and well designed course. I just feel that covering mathematical intricacies could help in better understanding of the concept and its application. Also I feel that this course of the specialization being very application based lacked coding exposure.

Jul 28, 2020

Nice designing of the course. The perfect combination of mathematics and applications. Nice videos, well explanation of concepts along with the application. A good bridge between mathematics and its applications. Thanks to professors and Imperial College London.

Nov 09, 2019

This course is perfect for those who prefer to understand the intuition behind multivariate calculus, visualize the power of gradients in optimizing functions, and apply calculus to machine learning with robust understanding of underlying mathematical concepts.

Feb 17, 2019

This course delivers its promise it is very crisp and concise. After completing this course I just feel I have remembered all vector calculus taken in my engineering maths (which is almost 8 years back) :)

I highly recommend this course to getting started ML/DL.

Jun 25, 2019

good mathematics course, but the things and concepts are explained in a very abstract way. Need to think a lot on your own while solving the quizzes as the videos are not going to help. Most of the concepts i learnt were from the quizzes rather than the videos

Apr 13, 2018

Even though in the beginning calculus seems to be confusing, because of the difficulty of the content, do not give up, I can guarantee that this course is the best way to learn calculus. The content is presented in a creative and fascinating way. Unmissable.

Jan 14, 2020

An excellently simple explanation of concepts of linear algebra. 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.

Nov 28, 2019

I found this course really useful and concise, straight to the concepts that are used in machine learning. The lecturers speak clearly and give very intuitive views on abstract concepts that I had trouble understanding before. I would totally recommend it.

Aug 04, 2019

The course began quite straightforwardly, and became progressively more challenging. I would recommend to others that they continually practice their skills at finding partial derivatives, as that skill gets even more important as the class progresses.

May 24, 2018

Great course! Builds up logically from a soft introduction to practical applications of multivariate calculus for data analytics. I no longer feel intimidated when I look at an expression involving higher order partial derivatives in multiple variables!

Jun 03, 2018

A very useful introduction of the math behind Machine Learning, a must if you plan to understand the algorithms used in ML, as usual the teachers are very very talented, focus is put in the essential and comprehension comes intuitively, Great Thanks!

Jan 06, 2020

A very good introductory course that is giving insightful explanations of how something is done and why. I especially enjoyed the part on gradient descent that was part of multiple modules. Very engaging instructors make learning easy and motivating.

Feb 02, 2020

Fantastic course, got to know the underlying maths behind complex ML algorithms, which was always a grey area to me, the instructors clearly explained each topic, which is a definitely a must add on skill to your journey towards Data Science career

Jul 10, 2020

I think this is one of the best course for understanding the calculus behind the machine learning algorithms. This also helps me understanding the back propagation, which is considered to be very painful topic for people not from maths background

Jul 25, 2019

It's challenging, specially about the week 4. But it's very possible to conclude successful. I just have high school and I finished the course with 100% of grade. My hint is: algebra is very important, but code can help you with this subject.

Mar 26, 2020

I've always felt intimidated by maths and it stopped me from really understanding machine learning and the different algorithms used. This course does a great job of making calculus understandable and demonstrates why it is so useful for ML.

Jul 16, 2020

The instructors are very enthusiastic and novel in their approach to teach which makes it very enjoyable to learn from them. Looking forward to completing this specialization and then learning more about ML and AI.

Thank you so much Coursera

Dec 10, 2019

standard short and crisp course. will do the job for what it is designed for. great explanations by mr. sam cooper and his visualization team at imperial. and mr.david also done a great job. overall worth spending funny jelly belly time.

Sep 05, 2018

Although difficult, this course makes sense of what is happening under the hood in training machine learning models. Instructors explain things well and the assignments gave opportunities to practice. I thoroughly enjoyed this course.

May 15, 2020

The thing I love about this course and the previous one, is how they make these heavy equations and stuff that we learn in school and university meaningful.

The instructors are very good, and the topic was handled perfectly. Well Done !