Chevron Left
Volver a Mathematics for Machine Learning: Multivariate Calculus

Opiniones y comentarios de aprendices correspondientes a Mathematics for Machine Learning: Multivariate Calculus por parte de Imperial College London

5,144 calificaciones
921 reseña

Acerca del Curso

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....

Principales reseñas


25 de nov. de 2018

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.


12 de nov. de 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.

Filtrar por:

51 - 75 de 925 revisiones para Mathematics for Machine Learning: Multivariate Calculus

por David S

21 de feb. de 2021

A solid course, recommended for those who want a deeper understanding of the math behind machine learning. It is well taught and organized, with many quizzes so students work through problems themselves,


a) don't think for a moment that a six minute video can be absorbed in six minutes, or a quiz can be completed in the suggested time. From my experience, count on taking twice as long

b) there are so many concepts introduced that I needed to refer a number of times to outside resources like Khan Academy or 3 Blue 1 Brown

Overall, a worthwhile course.


por Nabil C

25 de jun. de 2022

D​avid and Sam are amazing: The found the right balance between bulding up intuition and mathematical rigor. Also their use of coding labs is spot on: Not too much coding language related complexity that would distract from the real objectives of the course, while not making out of the labs a trivial exercise of code copy/paste.

W​hile I did Multivariate Calculus in depth back in University, that was 30 years ago, and I needed a good refresher before taking on some advanced ML/AI courses. This Maths for ML specialization did hit the spot.

por Khubaib A

29 de jul. de 2020

You will need the basics of Calculus in place. You can't just wake up and start Calculus with this course. With that said, the basics covered serve to be a good revision of the calculus. Certain applications such as the Neural Networks have been done hastily as others say on the forums (and I wholeheartedly agree) but then again this is not a course on Machine Learning. still some more examples from the instructors wouldn't hurt :) The exercises are great. Neither too hard nor too tough.

por Jaiber J

17 de abr. de 2020

Simply excellent course. The breadth of topics one needs to cover is astounding. I liked the way the topics and ordered, and following a common structure. The best part is the assignments - one really needs to understand every word of what the instructor says to solve it. They are tough in general to anyone who's done their bachelors/masters long time ago. For those who are not used to programming, the assignments can be difficult.

por Alina I H

9 de dic. de 2020

Amazing instructors and well designed course. Definitely a recommendable course to get intuitive knowledge on mathematical concepts that are relevant for machine learning. What I especially loved about it: it neither went too much into annoying and exhausting detail, nor was it simple. If you take this course, take some time to concentrate and get the brain cells running - will be a satisfying and rewarding experience! 11/10!

por 채영

23 de jun. de 2022

It took me at least 3 hours every day to understand and absorb the contents. It's that I'm not a native English speaker and I'm almost in the dark about mathmetics which is covered at university. Nevertheless, every step in the course was worth investing. I could know why I, as a would-be developer, should understand and keep mathmetics in my head. I downloaded all videos of this course and I'm gonna repeat them.

por Thuy T N

7 de ago. de 2020

This is my first encounter with Multivariate Calculus and surely the course has been extremely helpful beginner-friendly. I recommend investing in practical mathematics courses as this specialization if you are new to machine learning field. You will be equipped with enough math background and should feel confident to enter more technical machine learning/deep learning courses.

A truly fundamental stepping stone!

por Kerem E Y

31 de dic. de 2020

I learned limit, derivatives and integrals in high school. Afterwards, I took a few calculus lessons at university. However; I have never got a chance to see this theoretical background to put into practice. For this reason, I have never learned the essence of which means is calculus. I wouldn't have gotten a detailed education on this topic anywhere in Turkey. It was crucial for me, thank you for all !

por Reeshad M

6 de jul. de 2021

The videos are well designed and are direct in teaching the course material. For those with Calculus experience, it acts as a nice refresher and further expands it through higher dimensions. For those planning to learn more about Machine Learning and data science, the course also bridges mathematical gaps. Overall, I learned a lot and had fun while taking the course.

por Onkar A

20 de may. de 2020

Awesome course, so much to learn, and all concepts built up from basic, had fun with all assignments and stand-pit like interactive things, really boosted the understanding, i felt that prof. copper's speed of teaching was fast for me persoanlly , i had to pause many times and think what he said, but prof. david's pace was perfect for me, both instructors are great!

por David A E G

21 de ago. de 2020

A beautifully designed course, in which I could strongly settle the principles behind Linear Regression and Neural Networks. It did a wonderful job, filling the gaps I had from some other material I had checked on the web, but that was too technical, from a beginner's point of view. I feel so motivated by this course, that I will finish the specialization!

por Douglas W

4 de may. de 2020

Such an impressive set of instructors! I loved the enthusiasm at which the material was taught and injections of British humor. Now, this is not an easy course, but one that requires work. Plan on reacquainting yourselves with pencil, paper and practice. So, do the work, repeat videos when required, rely on classmates in the forums and you'll do fine.

por Ludovic G

7 de dic. de 2020

Simply brilliant ! Although the exercises might tend to be fairly simplistic, the quality if this course is top-notch. I truly believe it is one of the best material out there to get a grasp on fundamental concepts underpinning machine learning and data science.

I would definitely recommend the entire specialisation to anyone interest in this field.

por Manas G

15 de jul. de 2020

This is legitimate the best course on coursera. The video production and animations are beyond words. Also the amount of efforts put into quizzes and assignments is clearly visible. They are soo much helpful in understanding and practicing of the concepts taught. I loved doing this course. I wish there were more courses like in this specialization.

por Carlo G

12 de abr. de 2022

G​reat course about multivariate calculus and its application in machine learning. This completes very well the math side of things with other courses about machine learning, like from Andrew Ng. The instructors are great, the explanations clear and I like very much the code exercises! Can't wait to start the 3rd course of this specialisation.

por Aileen F

27 de nov. de 2020

Highly recommend it for engineering students or even graduates, since some schools in my country do not teach some of these topics and programming in their engineering programs. The discussion accompanied by graphical and interactive tools really helped me understand some of concepts. The quizzes and assessment focus on the important points.

por Camilo M

29 de jul. de 2020

The explanations are very clear and intuitive, the teachers explain very well and give guidelines so that you can do your own analysis and experimentation. The programming exercises are not complex but you must pay attention and take notes. So far both courses (linear algebra and multivariate calculation) are very, very good.

por Natasha M

10 de abr. de 2021

Probably my favorite course series on Coursera! Even though I already took calculus and algebra years ago, I feel like I have gained a greater intuition through this and the previous algebra course. These are probably not introductory courses, but more to gain a deeper intuition of using calculus for machine learning.

por Adithya P

26 de sep. de 2020

The instructors are amazing, they make things quite easy to understand and the assignments would give a proper measure of your understanding of the lectures. The content covered in the course gives you a perfect idea of visualizing 3d or multidimensional models(data). The forum has a healthy discussion on the subject.

por Idris R

28 de oct. de 2019

Fun and challenging course! It's priceless to learn all the math behind neural networks and other machine learning algorithms without having to learn all of calculus and all of linear algebra. Those are large fields and having the material presented in a way that focuses on the most relevant pieces is hugely valuable.

por Agamjyot C

16 de jun. de 2020

This is a must take course, if you want an insight into how the world of machine learning really works. This MOOC focused more on the intuition rather than just deriving out expressions for the heck of it. Everything has been explained in a very nice and simple manner, I have learned a great deal from this course.

por Peter K

18 de dic. de 2021

I appreciate the work of the course team. Many thanks. It is a great job. But I would list explicitly all the additional materials that could help to understand each week objectives. I mean such links to Khan Academy or other sources that could be relevant. Some videos could be expanded started from chapter 4.

por Kuntal T

13 de dic. de 2020

If you want to see the "Art of teaching", you must take or go through this course. Prof. Dye and Prof. Cooper explained the subject in a very nice way and I think every undergrad should take this course to clarify their understanding and for any person who whats to teach much watch it to learn how to teach.

por Umesh S

11 de dic. de 2020

Excellent course !! .. nice balance of mathematics and intuition building. Pace is fast but its fun. Some assignments are challenging but very rewarding once you get it right. Will recommend to all data science enthusiasts to go through this course to build right base before digging deep in ML algorithms

por Taranpreet s

17 de sep. de 2020

I was quite satisfied with the learnings from the course 1 of the specialization, this course amazed me about how the calculus and linear algebra are knitted together to solve optimization problems efficiently. Quizes are very helpful in reinforcement of the concepts. Instructors are great as well.