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返回到 Mathematics for Machine Learning: Multivariate Calculus

学生对 Imperial College London 提供的 Mathematics for Machine Learning: Multivariate Calculus 的评价和反馈

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5,737 个评分

课程概述

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....

热门审阅

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.

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.

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451 - Mathematics for Machine Learning: Multivariate Calculus 的 475 个评论（共 1,017 个）

创建者 Yujin Y

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Nov 12, 2022

Had a lot of fun through this course. Look into other courses.

创建者 Md. A A M

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Aug 20, 2020

Fantastic effort to teach such a great way. Highly Recommended.

创建者 Thomas L

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Nov 4, 2019

Brilliant course that covers so much in such a short time span.

创建者 Jevon K M

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Mar 9, 2019

My current (2019.03.09) employer hates it. Therefore I love it.

创建者 Tich M

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Jan 2, 2019

great course, great teachers. they break things down very well!

创建者 Hao H

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Sep 17, 2023

Great course, thanks the teachers and Coursera for this course

创建者 Tao S

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Feb 8, 2021

This course is excellent! I really enjoy Dr.Cooper's teaching.

创建者 Andrés M

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Jul 6, 2020

Coming from a BA in maths, I didn't expect it to be that good.

创建者 Aayush S

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May 29, 2020

Very good course for understanding basics of machine learning

创建者 AVICHAL S

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Mar 31, 2020

Course outline is well defined and instructors are very good.

创建者 Pavel S

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Dec 12, 2019

The best course of the module (perfect for non-matematicians)

创建者 Dominic D

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Jan 8, 2019

Very practical introduction to the subject, very well paced!

创建者 Matt T

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Jan 31, 2021

Great overview of the calculus topic needed to start in ML!

创建者 Morayo O

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Mar 28, 2020

I learned so much, more so on how calculus factors into ML.

创建者 Gordon C

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Oct 8, 2019

Clear and easy to follow, with practical examples and tasks

创建者 Shahriyar R

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Sep 9, 2019

Amazing in-depth explanations and insights. Thanks for all.

创建者 Kris S

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May 28, 2019

Very well taught, great flow of lectures, awesome teachers!

创建者 Joshua Z

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Jan 20, 2024

I took multivariate calculus before but now I truly get it

创建者 Raghunatha R t

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Aug 19, 2020

Excellent course and interesting applications with python.

创建者 XL T

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Mar 20, 2020

totally mind blowing and refreshing way to learn calculus!

创建者 Gyan D

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Oct 8, 2019

This course gave a good intuition of the mentioned topics.

创建者 Du L

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Aug 5, 2018

Super Great!!!

Clear illustration on multivariate calculus.

创建者 Evgeny ( C

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Jul 25, 2018

Great balance between presentation and excellent exercises

创建者 Amanda A

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Jun 18, 2021

Another brilliant course in this series! On to the next!

创建者 Sree H N

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Jun 9, 2020

One of the best courses I've come across on the platform.