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

4.7

2,177개의 평가

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327개의 리뷰

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.

Aug 04, 2019

Very Well Explained. Good content and great explanation of content. Complex topics are also covered in very easy way. Very Helpful for learning much more complex topics for Machine Learning in future.

필터링 기준:

교육 기관: ChristopherKing

•Apr 09, 2018

This is a good course for those people learned calculus before for a refresh.

교육 기관: francesc b

•May 25, 2018

Excellent 👍🏻👌🏻

교육 기관: Srikar V

•Apr 08, 2018

One of the best courses that I've done!

교육 기관: Iurii S

•Mar 26, 2018

Great introduction to Multivariate Calculus with a lot of visualizations to prop up the intuition

교육 기관: Shahzad A K

•May 24, 2018

Great course! Builds up logically from a soft introduction to practical applications of multivariate calculus for data analytics. I no longer feel intimidated when I look at an expression involving higher order partial derivatives in multiple variables!

교육 기관: Aleksey I

•Apr 22, 2018

Great course. Might be missing a few small details that will be hopefully filled in for the next iterations.

교육 기관: Ashish D S

•Apr 15, 2018

Excellent course!

I studied multivariate calculus during engineering. I hardly understood the concepts at that time, this course helped me understand and visualize what is going behind formulas.

교육 기관: Karthik

•Apr 23, 2018

Good reshres for calculus. I would recommend to take Khan Academy and then take this course.

교육 기관: Maged F Y A

•May 14, 2018

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

교육 기관: jinesh p

•Apr 02, 2018

Everyone should take this course before jumping into machine learning algorithms and applications.

교육 기관: Marvin P

•Apr 06, 2018

Just like the linear algebra one this course is absolutely awesome. The instructors provide structured insights, the assignments are well prepared. I'm amazed how much fun math can be!

교육 기관: Giuliano L P

•Apr 13, 2018

Even though in the beginning calculus seems to be confusing, because of the difficulty of the content, do not give up, I can guarantee that this course is the best way to learn calculus. The content is presented in a creative and fascinating way. Unmissable.

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교육 기관: J G

•Apr 24, 2018

It is a very good course about the Mathematics behind the Machine Learning models.

교육 기관: laszlo

•Apr 30, 2018

Really helpful and informative course. Different from the traditional math course, this course focuses on the intuitive understanding of math rather than the calculation. The calculation part are done by python code, which lays a foundation for further machine learning course and shows how the mathematical concepts are used in practice.

교육 기관: Chi W

•May 17, 2018

Excellent course! It helps understand to take the sandpit as an example for learning Jacobian, Hessian and steepest algorithm stuff. More than boring math formulas.

교육 기관: Timo K

•Apr 03, 2018

Just a great course for getting you ready to understand machine learning algorithms. The chapter on backpropagation is simply outstanding and the programming assignments are awesome!

교육 기관: HARSH K D

•Jun 26, 2018

good

교육 기관: Nigel H

•Apr 18, 2018

A change in staff from Imperial but the same enthusiasm; high standards of teaching mean you are going to get a lot from this course. Lots of examples and the practice quizzes really help with the consolidation. Great stuff.Thanks

교육 기관: Xiaoyuan C

•Jun 05, 2018

Fabulous applied mathematics course! It is so interesting that I cannot believe that it is a mathamatical course.

교육 기관: Вернер А И

•Mar 17, 2018

Excellent course. The material is taught in a precise, clear and intuitive manner. It would be great if a summary of the course will be given in form of some document.

교육 기관: ignacio

•Jun 30, 2018

Excellent way of explaining such abstract concepts.

교육 기관: FRANCK R S

•Jun 03, 2018

A very useful introduction of the math behind Machine Learning, a must if you plan to understand the algorithms used in ML, as usual the teachers are very very talented, focus is put in the essential and comprehension comes intuitively, Great Thanks!

교육 기관: Shuang D

•May 08, 2018

excellent course!

교육 기관: Joe E

•May 28, 2018

Great class and great instructors.

교육 기관: 林澤佑

•Mar 12, 2018

Review course for multivariate calculus and basic optimization method used for curve fitting. Suggest to provide more hint for programming assignment.