Back to Mathematics for Machine Learning: Multivariate Calculus

4.7

stars

3,638 ratings

•

634 reviews

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....

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.

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.

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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 10, 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 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 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 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

•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 Yuchi C

•Feb 23, 2020

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

By María J S G

•Aug 10, 2019

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

By Kovendhan V

•Jul 11, 2020

This is a must course to be taken up for AIML enthusiasts. Will greatly help before listening to Andrew Ng in Machine Learning course.

By Jean P F M

•Jun 28, 2020

Great course!! It was challenging, but as any good challenge the reward is worth it. Thanks for the opportunity of learning with you!!

By Abhilash V

•Mar 27, 2018

Good short videos and have great some practical assignments in python.A good intro and can be a good refresher to calculus for you.

By Jeferson S

•Mar 23, 2019

This course, took me deeply to the machine learning world, besides that It built up a strong bases to keep studying machine learning.

By JUNXIANG Z

•May 16, 2019

As a physics graduate, this course serves a fresh up in calculus and optimisation, which is essential for studying machine learning.

By Krishna K K

•May 08, 2020

Great course for deep learning engineers,cover all the fundamentals of calculus required for learning machines.Thanks to Professors

By Grigoraș V

•Dec 29, 2018

The professors are great! Wish we had part of such enthusiasm all throughout high-school. I bet people would enjoy math a lot more.

By Aymeric N

•Nov 12, 2018

Great lectures augmented with interesting and practical coding assignments. I really enjoyed this course on multivariate calculus.

By Gauri S

•Nov 24, 2019

It is a good course to understand where Calculus can applied to machine learning. It inspires me to pursue a MS in Data Science.

By Shaik R

•Apr 01, 2020

Mr. Sam Cooper and Mr. DavidDye's teaching are Simply awesome. Looking Forward to completing this specialization. ❤ from India.

By Vijayakumar

•May 19, 2020

Thank you professors for your nice explanation. I hope to see you again with in depth of machine learning and neural networks.

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