Mathematics for Machine Learning: Multivariate Calculus に戻る

4.7

1,782件の評価

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266件のレビュー

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....

Nov 13, 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.

Nov 26, 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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by Mohamed H

•Aug 05, 2019

Fantastic

by María J S G

•Aug 10, 2019

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

by Abdul W

•Aug 14, 2019

Efficient tutors who were able to inculcate interest in me towards finding out the roots of machine learning algorithms.

by Chokdee S

•Aug 14, 2019

It's really great course who want to study gradient decent using multivariate calculus from the ground up.

by Sidhant K R

•Aug 17, 2019

The most fundamental course on Machine Learning that I have done so far!

by sudipta p

•Aug 16, 2019

Excellent.

by Gopalan O

•Aug 18, 2019

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

by mnavidad

•Nov 25, 2018

This course was super hard but worth it...

by Hemant D K

•Dec 17, 2018

Its good.

by Paulo G

•Nov 29, 2018

great content, but the grader software needs some improvement

by Wenyuan Z

•Jan 11, 2019

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

by Mark R

•Jan 03, 2019

Good grounding in fundermental material needed for ML

by Prashant D

•Feb 17, 2019

Good course. The lecturer uses a number of illustrations and has a nice easy style to explain the key ideas. Overall enjoyable

by Arun I

•Mar 03, 2019

Good course to understand the basic mathematics terms and a refresher for high school math with some technical terms.

by Dan L

•Mar 30, 2019

The course accomplishes its goal of connecting concepts in calculus to machine learning, and is appropriately paced for students who have covered calculus in the past and are seeking a refresher or deeper understanding of its applications to real-world problems. For those who don't already have a certain minimum familiarity with the mathematics, however, the course will probably move at too fast a pace.

by Satpal S R

•Jan 30, 2019

This was a great course for learning multivariate calculus required for Machine Learning. I am thankful to the creators of this awesome course.

by Dmytro B

•Feb 11, 2019

Very helpful to review and get introduced to mathematical concepts behind machine learning. There is a fair bit of practical exercises as well. The only thing I am less happy about this cousre was a lack of additional suporting materials and references to other resources to help gain more knowledge on the subject.

by Patrick F

•Feb 01, 2019

Really good course, would recommend! 4 Stars, because there is no written transcript with the Formula and examples in the videos available.

by Hariharasudhan A S

•Feb 12, 2019

Really good for fundamentals, the assignments were too easy though

by danthedoubleD

•Mar 14, 2019

hopefully it is useful

by Miguel V

•Mar 16, 2019

I think Samuel Cooper is an amazing instructor. However, the last two weeks taught by David Dye were very difficult to follow. I think David should improve his explanations because I did not enjoy too much his course on linear algebra, and this course was great until he started with the last two weeks.

by Angelo O

•Dec 05, 2018

Nice refresher! Excellent instructors! Not recommended as a first Multivariate Calculus course though. I would go for MIT OpenCourseware first.

by George K

•Sep 21, 2018

Lack of support from the staff. Some parts/lectures are not clearly explained (for example, constrained optimization) and some quiz questions are not directly related to the course content. Otherwise, it's a very good course.

by Vignesh N M

•Sep 12, 2018

It was a good course compared to other two courses of this specialization.

by PEI-YUAN C

•Sep 29, 2018

Along with the advanced and popular technique, this course gives me impressive insight over how machine learning works. But it would be much better if the concept in linear algebra combines more with this course.