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

4.7

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387개의 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 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.

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: 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: Yuchi C

•Feb 23, 2020

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

교육 기관: 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

교육 기관: Abhilash V

•Mar 27, 2018

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

•Mar 23, 2019

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

•May 16, 2019

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

교육 기관: Grigoraș V

•Dec 29, 2018

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

•Nov 12, 2018

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

교육 기관: Gauri S

•Nov 24, 2019

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

교육 기관: Dhritiman S

•Nov 29, 2019

The course was excellent. I only wish the final few lessons covered Matrix equations for linear and non-linear least squares.

교육 기관: Gergo G

•May 01, 2019

Very good course on basic mathematics for machine learning. Good examples, some homework and very enthusiastic professors :)

교육 기관: Liam F

•Mar 24, 2019

Very well put together, a bit difficult in certain sections but all mysteries can be unraveled by a quick google. Thank you!

교육 기관: Abdul W

•Aug 14, 2019

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

교육 기관: sumit

•Oct 09, 2019

Really Challenging courses. The Last three weeks were really difficult to complete but it really gave some detail idea.

교육 기관: Vibhutesh K S

•May 18, 2019

I think neural networks was unnecessary. It was very concise to understood by anybody without prior knowledge about it,

교육 기관: 丁榕

•Sep 05, 2018

Totally like it!!!! Really fundamental and both of the two lecturers have made every important key points quite clear.

교육 기관: Mithun B

•Oct 15, 2018

Really liked the course. If there are more of neural network course that Imperial College can come up would be best.

교육 기관: Sameen N

•Feb 22, 2019

It us good course and gave me basic understanding of multivariate calculus. It provide insight of gradient descent.

교육 기관: imran s

•Dec 02, 2018

Well explained and I would say also https://www.mathsisfun.com/algebra/taylor-series.html to get some more details.

교육 기관: Hamza a

•Oct 23, 2018

This one is a very good course and also very well organized. I also have used khan academy for making things clear

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: Nelson C S

•Feb 13, 2020

A very good course. Also, It is a very important for those who want to know how machine learning algorithms work.

교육 기관: Serge H k

•Dec 12, 2018

I love the assignments. It was fun being able to translate mathematics equations and algorithms into python code

교육 기관: Shraavan S

•Jan 06, 2019

The intuition is explained very clearly. Graphs in 2D and 3D are used effectively to clearly express the idea.

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.