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Back to Mathematics for Machine Learning: Multivariate Calculus

Learner Reviews & Feedback for Mathematics for Machine Learning: Multivariate Calculus by Imperial College London

4.7
stars
5,542 ratings

About the Course

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....

Top reviews

DP

Nov 25, 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.

JT

Nov 12, 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.

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226 - 250 of 985 Reviews for Mathematics for Machine Learning: Multivariate Calculus

By Dr. S R J K

Jul 18, 2020

A very good course to understand the role of Calculus in various fields. Concepts were explained in a precise manner with interesting illustrations.

By Louis G

Jun 15, 2023

Nice course with very clear explanation of the mathematics required for ML. The coding exercises are very immersive and the results are satisfying.

By Sailesh N

Oct 16, 2019

I had very good experience learning this course. I have learnt the real life application of calculus. The explanation of each videos was very good.

By Yana K

Apr 11, 2019

Great course, very good introduction into calculus for ML. Great explanation of neural networks and math used for them. A bit tricky last 2 weeks.

By Saurav B

Nov 25, 2018

An intuitive introduction to multivariate calculus and its applications in Machine Learning - the perfect course for a budding computer scientist.

By Max B

Apr 20, 2020

I benefitted a lot from this course. I liked the fast pace and feel that I understand the math behind the machine learning algorithms better now.

By Mohamed R

Sep 10, 2018

one of the best courses I have ever had.

thanks to instractors and Imperial College London

thanks so much for that specilization it helped me alot

By Aaron B

Jun 9, 2018

Excellent class! I feel like I finally understand calculus after all the rote memorization I had in my high school and college calculus courses.

By Shaiman S

Apr 28, 2020

Mr. Sam Cooer and Mr. David dye made things very simple to learn. However, inclusion of some more numerical methods can make this course ideal!

By balaji r

Jun 10, 2019

That's some excellent course to take for! Awesome explanations for the concepts and I strongly recommend khan academy for further explanations.

By Amar n

Dec 11, 2020

Just Brilliant!!! Very well structured with very clear assignments. Doing the assignments is a must if you want to get clarity on the subject.

By Mark J T

Jan 25, 2020

The course is a very concise and excellent introduction to the calculus necessary. It answers a lot of questions with respect to optimization.

By Francesco N

Jul 3, 2023

Exceptional insights regarding the calculus aspect of machine learning. The way concepts are explained by the teachers is simply astonishing.

By Phạm N M H

May 23, 2019

This is one of three course in Mathematics for ML, it'll give you intuition for understand the true meaning of ML/DL/AI , it's all about math

By Samuel S

Oct 9, 2021

LOVE IT LOVE IT LOVE IT Thank you everyone from Imperial and all sponsors for making this course possible! Was absolutely BLESSED THANK YOU!

By Amartya M

Aug 30, 2020

Quite a good overview int the concepts. Lucid explanation and good quizzes. Would recommend Khan Academy Multivariate calculus on top of it

By Julio G

Apr 13, 2020

Great introduction into optimisation. Looking forward to continuing with the 3rd course. Thanks Imperial College for having this available.

By Roshan B

Jul 23, 2019

An excellent review course for those who had not used calculus for a while. The derivation of the back propagation algorithm was excellent!

By Gopalan O

Aug 18, 2019

Excellent course on multivariate calculus and application of calculus in Machine Learning. Loved the assignments and the programming ones.

By Yuanfang F

Aug 24, 2019

Prof. Dye's presentation is so polished - the examples are exactly the type to help cover much ground, while building a strong intuition.

By Maged F Y A

May 14, 2018

a very good explanation of the required calculus basics for machine learning. moreover, it opens the way for the wide optimization world.

By Karthi V E

Nov 12, 2021

Really well structured course. The modules around Gradient Descent could have been a little slower, but overall great pace and teaching.

By Yuchi C

Feb 23, 2020

Very well structured and nicely explained. The assignments / quizzes are very helpful for deepening and strengthening the understanding.

By Mjesus S

Aug 10, 2019

Muy adecuado si estamos interesados en introducirnos en el mundo de los algoritmos usados en inteligencia artificial y machine learning

By Indranil A

Sep 6, 2021

I particularly liked the way the course has been structured to guide people towards machine learning from linear algebra and calculus.