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Mathematics for Machine Learning

Multivariate Calculus

This course is a part of Mathematics for Machine Learning, a 3-course Specialization series from Coursera.

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.

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Imperial College London

Rating 4.6 based on 211 ratings
Length 7 weeks
Effort 6 weeks of study, 2-5 hours/week
Starts Sep 16 (9 weeks ago)
Cost $49
From Imperial College London via Coursera
Instructors Samuel J. Cooper, David Dye, A. Freddie Page
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Mathematics
Tags Computer Science Algorithms Math And Logic

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What people are saying

According to other learners, here's what you need to know

machine learning in 32 reviews

a very good explanation of the required calculus basics for machine learning.

The calculation part are done by python code, which lays a foundation for further machine learning course and shows how the mathematical concepts are used in practice.

Great stuff.Thanks A quick short introduction to multivariate calculus and few machine learning techniques, but without much detail mathematical proofs for some ideas.

Just a great course for getting you ready to understand machine learning algorithms.

Everyone should take this course before jumping into machine learning algorithms and applications.

The course is a great introduction to how one can translate pre-learned mathematical concepts into machine learning.

Very good course on basic mathematics for machine learning.

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multivariate calculus in 19 reviews

Builds up logically from a soft introduction to practical applications of multivariate calculus for data analytics.

Excellent course!I studied multivariate calculus during engineering.

excellent Review course for multivariate calculus and basic optimization method used for curve fitting.

Quality course that will leave you feeling confident in multivariate calculus and analytics.

It us good course and gave me basic understanding of multivariate calculus.

This was a great course for learning multivariate calculus required for Machine Learning.

very good introductory course to Multivariate Calculus Well the course is generally good, the only problem is that David sometimes may just skip the process and lack more explanation when performing the calculation, it's easy to lose track of what he is calculating if not reviewing the video over and over again, but anyway, the whole class is worth recommendation, thank you for your teaching, professors Very practical introduction to the subject, very well paced!

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linear algebra in 9 reviews

the basic concepts are explained clearly, but the step of the lecture became more fast than the course of linear algebra.

Just like the linear algebra one this course is absolutely awesome.

A bit more challenging than the Linear Algebra course.

I have leant single variable calculus and linear algebra (freshman year difficulty), and this course is challenging but doable for me!

But it would be much better if the concept in linear algebra combines more with this course.

This is way better than the linear algebra course in this specialization.

Highly recommend Following on from the Linear Algebra course, this is equally excellent.

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imperial college in 5 reviews

Another fantastic course by Imperial College.

Well done and kudos to Imperial College for taking the initiative.

If there are more of neural network course that Imperial College can come up would be best.

one of the best courses I have ever had.thanks to instractors and Imperial College Londonthanks so much for that specilization it helped me alot Fantastic overview/refresher of multivariate calculus, with links to ML / neural nets throughout.

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partial derivatives in 3 reviews

I no longer feel intimidated when I look at an expression involving higher order partial derivatives in multiple variables!

exercises on partial derivatives need to be focused more on various aspects of partial differentiation rather than on taking partial derivatives of some complicated functions.

Again, the main enjoyment comes from seeing techniques learnt at school (partial derivatives, Taylor series, Newton-Raphson, etc) actually being used in practice.

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Coursera

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Imperial College London

Rating 4.6 based on 211 ratings
Length 7 weeks
Effort 6 weeks of study, 2-5 hours/week
Starts Sep 16 (9 weeks ago)
Cost $49
From Imperial College London via Coursera
Instructors Samuel J. Cooper, David Dye, A. Freddie Page
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Mathematics
Tags Computer Science Algorithms Math And Logic

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