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Вернуться к Mathematics for Machine Learning: Multivariate Calculus

Отзывы учащихся о курсе Mathematics for Machine Learning: Multivariate Calculus от партнера Имперский колледж Лондона

Оценки: 4,918
Рецензии: 881

О курсе

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....

Лучшие рецензии

25 нояб. 2018 г.

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.

12 нояб. 2018 г.

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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426–450 из 884 отзывов о курсе Mathematics for Machine Learning: Multivariate Calculus


27 июля 2020 г.

Good introductory course on calculus and optimisation

автор: Deepak T

20 мар. 2020 г.

Taylor Expansion, Gradient Descent and further more:)

автор: Ashutosh P

15 сент. 2018 г.

Great comprehensive course for Mathematics behind ML.

автор: John C B

19 июля 2021 г.

well presented material with nice, clean assignments

автор: John V

2 апр. 2020 г.

One of the best practical math courses I have taken

автор: Марья Б

11 февр. 2020 г.

Amazing course, everything is very well explained :)

автор: Steve G

2 февр. 2019 г.

Great course learned a lot Teacher was very engaging

автор: DIAZ R G A

1 окт. 2020 г.

excelente curso con todos los temas bien explicados

автор: ignacio

29 июня 2018 г.

Excellent way of explaining such abstract concepts.

автор: Charchit S

2 дек. 2020 г.

This course give's you a head start in ML journey.

автор: Adryan R A

6 окт. 2021 г.

One of the best course for mathematic in coursera

автор: Anbu V

4 мар. 2019 г.

Good revision for the calculus' application in ML

автор: anirbid g

1 окт. 2018 г.

great course, wonderful instructors. thanks much.

автор: Matthew S

20 сент. 2020 г.

A really enjoyable and well put together course!

автор: Nitish T

12 июля 2019 г.

Very relevant course. It was very helpful to me.

автор: Andreas Z

11 июля 2018 г.

Just as good as the first course of this series.

автор: Osama K

11 дек. 2020 г.

Thanks, it was a lot of fun taking this course.

автор: Felipe C

24 мар. 2020 г.

Great course and the materials are very helpful

автор: Linda D

22 февр. 2020 г.

Great course for some general methods and math.

автор: Apoorv M

10 апр. 2021 г.

awesome instructors with well explained course

автор: Hyun H M

17 окт. 2020 г.

Great course to understand vector and calculus

автор: Neelam U

1 сент. 2020 г.

I loved the application aspect of this course!

автор: Archana D

6 мар. 2020 г.

it was great to have the formulas as reference

автор: Mohammad M

24 июля 2018 г.

Perfect start point to learn machine learning.

автор: Bruno F

14 окт. 2018 г.

Nice course. Very useful for machine learning