Вернуться к Mathematics for Machine Learning: Multivariate Calculus

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

4.7
звезд
Оценки: 4,734
Рецензии: 840

## 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

JT
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.

DP
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.

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## 201–225 из 839 отзывов о курсе Mathematics for Machine Learning: Multivariate Calculus

автор: Aaron B

9 июня 2018 г.

Excellent class! I feel like I finally understand calculus after all the rote memorization I had in my high school and college calculus courses.

автор: Shaiman S

28 апр. 2020 г.

Mr. Sam Cooer and Mr. David dye made things very simple to learn. However, inclusion of some more numerical methods can make this course ideal!

автор: balaji r

10 июня 2019 г.

That's some excellent course to take for! Awesome explanations for the concepts and I strongly recommend khan academy for further explanations.

автор: Amar n

11 дек. 2020 г.

Just Brilliant!!! Very well structured with very clear assignments. Doing the assignments is a must if you want to get clarity on the subject.

автор: Mark J T

25 янв. 2020 г.

The course is a very concise and excellent introduction to the calculus necessary. It answers a lot of questions with respect to optimization.

автор: Phạm N M H

23 мая 2019 г.

This is one of three course in Mathematics for ML, it'll give you intuition for understand the true meaning of ML/DL/AI , it's all about math

автор: Amartya M

30 авг. 2020 г.

Quite a good overview int the concepts. Lucid explanation and good quizzes. Would recommend Khan Academy Multivariate calculus on top of it

автор: Julio G

13 апр. 2020 г.

Great introduction into optimisation. Looking forward to continuing with the 3rd course. Thanks Imperial College for having this available.

автор: Roshan B

23 июля 2019 г.

An excellent review course for those who had not used calculus for a while. The derivation of the back propagation algorithm was excellent!

автор: Gopalan O

18 авг. 2019 г.

Excellent course on multivariate calculus and application of calculus in Machine Learning. Loved the assignments and the programming ones.

автор: Yuanfang

24 авг. 2019 г.

Prof. Dye's presentation is so polished - the examples are exactly the type to help cover much ground, while building a strong intuition.

автор: Maged F Y A

14 мая 2018 г.

a very good explanation of the required calculus basics for machine learning. moreover, it opens the way for the wide optimization world.

автор: Yuchi C

23 февр. 2020 г.

Very well structured and nicely explained. The assignments / quizzes are very helpful for deepening and strengthening the understanding.

автор: Mjesus S

10 авг. 2019 г.

автор: Kovendhan V

11 июля 2020 г.

This is a must course to be taken up for AIML enthusiasts. Will greatly help before listening to Andrew Ng in Machine Learning course.

автор: Jean P F M

28 июня 2020 г.

Great course!! It was challenging, but as any good challenge the reward is worth it. Thanks for the opportunity of learning with you!!

автор: Abhilash V

26 мар. 2018 г.

Good short videos and have great some practical assignments in python.A good intro and can be a good refresher to calculus for you.

автор: Jeferson S

23 мар. 2019 г.

This course, took me deeply to the machine learning world, besides that It built up a strong bases to keep studying machine learning.

автор: JUNXIANG Z

16 мая 2019 г.

As a physics graduate, this course serves a fresh up in calculus and optimisation, which is essential for studying machine learning.

автор: Krishna K K

7 мая 2020 г.

Great course for deep learning engineers,cover all the fundamentals of calculus required for learning machines.Thanks to Professors

автор: Grigoraș V

29 дек. 2018 г.

The professors are great! Wish we had part of such enthusiasm all throughout high-school. I bet people would enjoy math a lot more.

автор: Aymeric N

12 нояб. 2018 г.

Great lectures augmented with interesting and practical coding assignments. I really enjoyed this course on multivariate calculus.

автор: Sai P B L

28 авг. 2020 г.

Good beginner course for learning the fundamentals of mathematics involved in machine learning.

Would highly suggest this course.

автор: Gauri S

24 нояб. 2019 г.

It is a good course to understand where Calculus can applied to machine learning. It inspires me to pursue a MS in Data Science.

автор: Arnab S

11 сент. 2020 г.

This is a very good foundational course for anyone who wants to understand the idea behind the mathematics of Machine Learning.