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Mathematics for Machine Learning: Multivariate Calculus, Imperial College London

1,110 notes
166 avis

À propos de ce cours

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....

Meilleurs avis

par DP

Nov 26, 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.

par 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.

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168 avis

par Avinash

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.

par Prashant Dabholkar

Feb 17, 2019

Good course. The lecturer uses a number of illustrations and has a nice easy style to explain the key ideas. Overall enjoyable

par Hariharasudhan A S

Feb 12, 2019

Really good for fundamentals, the assignments were too easy though

par 희랑 이

Feb 12, 2019

I think this course will help me a lot.

par Dmytro Berko

Feb 11, 2019

Very helpful to review and get introduced to mathematical concepts behind machine learning. There is a fair bit of practical exercises as well. The only thing I am less happy about this cousre was a lack of additional suporting materials and references to other resources to help gain more knowledge on the subject.

par Jimmy Kumar Ahalpara

Feb 03, 2019

This is a great course to brush up your machine learning maths, this course describes backpropagation nicely and how its derived. Large part of this course is focused on optimization in which calculus is mostly used.

par Stephen Geier

Feb 02, 2019

Great course learned a lot Teacher was very engaging

par Patrick Frece

Feb 01, 2019

Really good course, would recommend! 4 Stars, because there is no written transcript with the Formula and examples in the videos available.

par Satpal Singh Rathore

Jan 30, 2019

This was a great course for learning multivariate calculus required for Machine Learning. I am thankful to the creators of this awesome course.

par David Hwang

Jan 28, 2019

They know what students want to learn and teach it well.