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Volver a Mathematics for Machine Learning: Multivariate Calculus

Opiniones y comentarios de aprendices correspondientes a Mathematics for Machine Learning: Multivariate Calculus por parte de Imperial College London

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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....

Principales reseñas

SS

3 de ago. de 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.

JT

12 de nov. de 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.

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826 - 850 de 928 revisiones para Mathematics for Machine Learning: Multivariate Calculus

por Manish C

26 de abr. de 2020

Excellent course for beginners who want to learn machine learning .

por João M G

31 de jul. de 2019

Weeks 1-4 are great! Weeks 5 and 6 are longer and less explanatory.

por Alex S

16 de ago. de 2018

Good course to learn about the mathematics behind machine learning.

por Jair J C C

26 de dic. de 2019

Excellent course, some parts in the last weekend were not so clear

por Hari

12 de feb. de 2019

Really good for fundamentals, the assignments were too easy though

por Rakesh V S

4 de ene. de 2020

Last week was very rushed. Should be more patient in teaching.

por Paulo G

29 de nov. de 2018

great content, but the grader software needs some improvement

por Prabhjot S A

2 de may. de 2020

First 4 weeks were awesome but last 2 weeks were mediocre.

por Harsh D

2 de jun. de 2019

Awesome course, just wish it had more info on hessian.

por Mark R

3 de ene. de 2019

Good grounding in fundermental material needed for ML

por William S

11 de ene. de 2020

Weeks 1-4 were great, 5-6 felt rushed and confusing

por Shariq A

24 de dic. de 2019

Good course ..but need to elaborate a little more

por Naseem A

20 de dic. de 2021

get confused when going to last part this course

por Tess P

14 de abr. de 2020

I would love to have more practice exercises

por SHIVANG S

25 de abr. de 2020

Programming assignments were not so useful

por mnavidad

24 de nov. de 2018

This course was super hard but worth it...

por Salah E

23 de jul. de 2020

again it is too hard and pushed my limits

por Kleider S V G

23 de ago. de 2021

A very orderly course, in my opinion.

por Kevin k

20 de ago. de 2021

P​rof Cooper is a master at his craft

por Eric G

16 de jul. de 2019

A brief but also very in-depth course

por sreekar

23 de oct. de 2018

Great instruction and good materials.

por Gurbaaz S G

14 de may. de 2021

it was good and interesting course

por Julia K

6 de oct. de 2019

A challenging but exciting course!

por Hizkia F C E

24 de mar. de 2022

it's better to add more examples

por Shivang G

1 de sep. de 2021

To the point and decent depth