Volver a Mathematics for Machine Learning: Multivariate Calculus

4.7

1,123 calificaciones

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170 revisiones

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....

por 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.

por 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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171 revisiones

por Allie Alexander Mussa

•Feb 20, 2019

Thank you!

por Bryan Stafford

•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 .

por Rafi Dudekula

•Feb 18, 2019

Great course! A bit more challenging than the Linear Algebra course.

por 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.

por 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

por Hariharasudhan A S

•Feb 12, 2019

Really good for fundamentals, the assignments were too easy though

por 희랑 이

•Feb 12, 2019

I think this course will help me a lot.

por 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.

por 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.

por Stephen Geier

•Feb 02, 2019

Great course learned a lot Teacher was very engaging

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