Voltar para Mathematics for Machine Learning: Multivariate Calculus

4.7

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2,637 classificações

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420 avaliações

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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por Fang Z

•Jul 11, 2019

I really love Samuel's teaching style. He strived to make people understood by showing a lot of graph and I can easily follow him step by step. However, David's teaching I couldn't follow up his mind much maybe because less explanations given during the lecture.

In addition, I found some quiz have huge amount of calculated amount which I really spent a lot time to verify the answer.

Finally, I hope more detailed explanations could be given if I made mistakes in some quiz so I could boost what I've learned so far.

Thanks,

Fang

por Hermes J D R P

•Feb 28, 2020

The first 4 weeks of the course were amazing: great content, clear explanations and fair and interactive assessment activities. However, the last 2 weeks weren't as good as the previous ones. That's why I don't give this course 5 stars. By and large, the first two courses of this specialization are the best resources available on the internet to learn the foundations of mathematics for Machine Learning. I recommend that instead of doing the last course, you had better try to read the related book wrote by Deisenroth.

por Saras A

•Jan 29, 2020

Good course. I wish it had more sections as in a total of 12 sections or weeks and more steps to gain a more thorough graphical understanding (and perhaps even a more mathematical/algebraic understanding however overall that's much easier for me on that front...).

From a Data Science or Machine Learning perspective Week 6 (linear regression and non linear regression with chi-squared methods etc) were the most interesting.

por 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.

por Matt P

•Jul 19, 2018

Great class - very informative and eye opening - even with quite a bit of linear algebra background. Really liked the eigenvector and eigenvalue section - great descriptions. I wish the neural network discussion went on a bit further. I found some of the programming assignments' instructions a bit vague and confusing - what should have taken a few minutes ends up taking a half hour.

por Aneev D

•Oct 19, 2018

This course is great in the sheer efficiency with which it goes through the content required to prepare you for machine learning. It builds an intuition for what's going on, which is amazing. Some parts are confusing, and I recommend looking at Khan Academy for the lectures on Jacobians and steepest ascent, and 3Blue1Brown for feedforward neural networks.

por 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

por Mihai R F

•Nov 01, 2019

Very valuable training course from the insight/intuition point of view. This is more of an overview of the calculus for machine learning giving the student a good direction of what to study and where to start from. I think that actually mastering the subject will require extensive additional exercises from other sources

por 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.

por Luis M V F

•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.

por Michelle W

•Nov 17, 2019

I would say this entire series is better advertised as a quick *review* of the pertinent concepts. Otherwise, someone with no background in the topics covered may struggle (unless they are particularly talented with quickly learning new mathematical concepts).

por Alexander L

•Mar 22, 2020

This felt like time well spent. A really good course which I should have taken before doing the Machine Learning Course by Andrew Ng. That would have made life easier.

Beware, the 'gradient of the learning curve' at any point during this course is steep.

por Sirigiri S K

•Jan 13, 2020

Need a bit more clarity in terms of integrating the calculus in the last week sessions.

I agree they are very good but would be great if there is some more additional clarity. And also some project using the whole course would be helpful.

por Ankit C

•Mar 28, 2020

It gives you a good head-start to the math required in Machine learning. Some major concepts are touched just on the surface level but the mathematics involved in those concepts is explained quite well. Overall, it's good experience

por SUJITH V

•Sep 16, 2018

Very good course to start of with mutivariable calculus basics. Helps to refresh your memory if already familiar with concepts, additionally helps in getting fresher perspective because of geometrical intuition presented very well.

por 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.

por Jacqueline B

•Apr 06, 2020

up to week 5 , it was masterpiece.

week6 (although it should be the most important one) was a mess and disappointing.. as it was not explainable, i couldn't link what is happening with previous weeks.. require to be enhanced

por Izzan D

•Mar 29, 2020

The first 3 weeks is really good, the fourth week is okay but the last 2 weeks is kinda confusing. The explanation is quite clear but it is quite hard to grasp the intuition and relationship between each material.

por 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.

por Girisha D D S

•Aug 26, 2018

I thoroughly enjoyed this course. The materials were good and the course content was good enough to pass all the assignments and quizzes. This is way better than the linear algebra course in this specialization.

por mrinal

•Jun 07, 2018

i think some of concepts touched the surface and it was difficult to get a deep understanding .Probably the course could have provided some external links for those topics where people could read .

por Ashish k

•Jul 28, 2019

Superb quality. The way instructors teach is really innovative. The course is good in terms of the area it covers but lacks depth, but is a good starting point if you want to dwell more in detail.

por Kalpak S

•Mar 08, 2020

I wish, Linear Regression was taught with a little more clarity. Seemed like too many things were happening. Otherwise, a very good course. Really enjoyed the back-propagation week.

por Xiao F

•Apr 23, 2018

the basic concepts are explained clearly, but the step of the lecture became more fast than the course of linear algebra. More detail proof and application of theory is expected.

por Arnaud J

•May 23, 2018

The course is still a bit young, some errors appear here and there sometimes, and some parts of it are a bit steep.

Otherwise, this is a good course, focused on derivatives.

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