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Mathematics for Machine Learning: Multivariate Calculus(으)로 돌아가기

임페리얼 칼리지 런던의 Mathematics for Machine Learning: Multivariate Calculus 학습자 리뷰 및 피드백

4.7
별점
5,314개의 평가

강좌 소개

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....

최상위 리뷰

JT

2018년 11월 12일

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

2018년 11월 25일

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.

필터링 기준:

Mathematics for Machine Learning: Multivariate Calculus의 948개 리뷰 중 226~250

교육 기관: balaji r

2019년 6월 10일

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

교육 기관: Amar n

2020년 12월 11일

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

교육 기관: Mark J T

2020년 1월 25일

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

교육 기관: Phạm N M H

2019년 5월 23일

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

교육 기관: Samuel S

2021년 10월 9일

LOVE IT LOVE IT LOVE IT Thank you everyone from Imperial and all sponsors for making this course possible! Was absolutely BLESSED THANK YOU!

교육 기관: Amartya M

2020년 8월 30일

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

교육 기관: Julio G

2020년 4월 13일

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

교육 기관: Roshan B

2019년 7월 23일

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

교육 기관: Gopalan O

2019년 8월 18일

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

교육 기관: Yuanfang F

2019년 8월 24일

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

교육 기관: Maged F Y A

2018년 5월 14일

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

교육 기관: Karthi V E

2021년 11월 12일

Really well structured course. The modules around Gradient Descent could have been a little slower, but overall great pace and teaching.

교육 기관: Yuchi C

2020년 2월 23일

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

교육 기관: Mjesus S

2019년 8월 10일

Muy adecuado si estamos interesados en introducirnos en el mundo de los algoritmos usados en inteligencia artificial y machine learning

교육 기관: Indranil A

2021년 9월 6일

I particularly liked the way the course has been structured to guide people towards machine learning from linear algebra and calculus.

교육 기관: Kovendhan V

2020년 7월 11일

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

교육 기관: Jean P F M

2020년 6월 28일

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

교육 기관: Abhilash

2018년 3월 26일

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

교육 기관: Jeferson S

2019년 3월 23일

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

교육 기관: JUNXIANG Z

2019년 5월 16일

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

교육 기관: Krishna K K

2020년 5월 7일

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

교육 기관: Grigoras V (

2018년 12월 29일

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

교육 기관: Aymeric N

2018년 11월 12일

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

교육 기관: Farhan F

2022년 3월 25일

This course for my opinion is very very very challengging, but i'm satisfied because this material is one of like and i love it.

교육 기관: SAI P B L E

2020년 8월 28일

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

Would highly suggest this course.