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Voltar para Mathematics for Machine Learning: Multivariate Calculus

Comentários e feedback de alunos de Mathematics for Machine Learning: Multivariate Calculus da instituição Imperial College London

4.7
estrelas
3,996 classificações
706 avaliações

Sobre o curso

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....

Melhores avaliações

DP

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.

SS

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.

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676 — 700 de 706 Avaliações para o Mathematics for Machine Learning: Multivariate Calculus

por Alfred S

Jan 13, 2019

Course would be prefect if there would not be technical issues with opening notebooks. It slows me down by 1 week. But content was really relevant to ML.

por Kumar S

Aug 09, 2020

Overall average course. Not that much good as expected because of David Dye. He was teaching very poor in this course as compared to course-1.

por TirupathiRao p

May 21, 2020

Last 2 weeks completely diverged. Failed to converge. I wish content was more elaborate.First course of this specialization was far better.

por MAYANK G

Jul 04, 2018

Role of discussion forum is very less. Please improve on that to have healthy participation. Otherwise, course content is really good.

por Nabijonov K T

Dec 07, 2019

first 4 weeks were good. Starting from week 5 course explanation was bad. Was required to watch other videos.

por Lieu Z H

Nov 18, 2019

Lecture videos are quite sparse, and the quizzes test things that they don't teach you in the lecture

por Saurabh M

Sep 29, 2020

A bit fast paced, could be much more beneficial with some added explanations.

por Lee j

May 23, 2019

Too fast to understand what instructors says.. but lecture contents are good

por Akeel A

Aug 29, 2020

It was a lot of fun at points. Would recommend to anyone else.

por Gurrapu N

Apr 07, 2020

Strong disconnect between teaching videos and assignments.

por joseph k

Apr 13, 2020

Course would enhanced if pdf's of lectures were provided.

por Alkis G

Jul 14, 2019

There is a decent space for course improvement.

por prudhvi

Jun 23, 2019

week 6 content is not clear at least for me .

por สิทธิพร แ

Jun 13, 2020

Week 5 and 6 Lecture quite poor

por Leigh F

May 29, 2019

Concepts not clearly explained.

por Aviv P

Dec 06, 2018

many topic were explained badly

por Vivek P D

Sep 10, 2019

Explanation is not in depth

por Mahmoud T

Mar 30, 2020

Dr.Sam Cooper is the best.

por Abdelftah M

Apr 05, 2020

Change the bald man.

por Rishabh J

Mar 08, 2019

Not very challenging

por Tianchi M (

Jul 04, 2018

NOT VERY SYSTEMATIC

por chanhee

Apr 17, 2020

It's nice

por Alexander M

Jan 23, 2020

.,

por Alois H

Jul 22, 2020

The material is great and very relevant to anything connected to data science, however, I didn't enjoy this course half as much as the first in the series.

It's way too dense, things appearing on the screen where it's not clear where they're coming from, explanations feel scripted and read out at high speed, frequently unclear.

If you're using screen shots for taking notes (as I do), that's not ideal either because they're writing on a glass pane while they're standing behind it.

I'm working full-time and had to take this course stretched out over a long time. Again, the presentation being so dense doesn't help there either.

All in all it feels like a published first draft of the course, it doesn't seem the instructors are trying to improve the course at all.

por Paul K M

Oct 24, 2019

I am not sure if this course is for people who know calc, and want to learn python coding or people who know coding and want to learn some calc? Frankly it isn't a great course for either group. I knew some calc, and some python going in, and I did expand my knowledge and gain some useful practice. But it left me craving rigor.