Back to Mathematics for Machine Learning: Multivariate Calculus

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5,574 ratings

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....

JT

Nov 12, 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.

DP

Nov 25, 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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By Shintya R R M

•Mar 6, 2021

This course is good to start learning Machine Learning. There are also labs practice so that I can acquire deeper understanding by the visualization. However, some materials are not explained clearly, such as Newton-Raphson method and Lagrange Multiplier.

By Glendronach 3

•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.

By 胡震远

•Aug 30, 2020

Generally, it is a good course. Many new tools and fancy representation method, but for mathematical idea and explanation, it is just too simple. Maybe the biggest contribution to me is that It lets me know the Kahn Academy and 3b1b courses.

By Aditya J

•Apr 13, 2020

Could have explained in a way that the audience requires a slower and better and little more in-depth explanation. Some places felt a little rushed, so had to spend more time in forums and other resources to get more idea. Overall was great.

By Tai N

•Jun 25, 2021

This course assumes some knowledge of Python. Some topics are taught quite quickly, and overall this is not a comprehensive course. A good introduction to multivariate calculus. I suggest learners use Khan's Academy in supplement to this.

By 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.

By 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

By sujith

•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.

By Switt K

•Jul 27, 2020

Good details, great at building intuitions. Instructors are pleasant to listen to :)

As expected, it's enough to get you going in the right direction, that if you want to know more, you'd have enough knowledge to build on from.

By Γιώργος Κ

•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.

By Jacqueline B

•Apr 6, 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

By Jae N

•May 5, 2022

This was a good course. The instructors kept me interested in a rather dry subject. The exercises were well designed. There are courses on Coursera which are not worth the time. This course is not one of those.

By 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.

By Peiyuan 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.

By 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.

By Igor C A d L

•Apr 3, 2022

All was great until weeks 5 and 6. For these weeks, there weren't enough explanations in order to really understand the subject. Some very important steps were simplified, which made understanding difficult.

By Mrinal S

•Jun 7, 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 .

By 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.

By Keshav B

•Jul 24, 2020

Very informative refresher on the basics of differentiation, though some of the later topics could have been fleshed out more (i.e. Taylor Series, Lagrange Multipliers, etc). Overall very good.

By Marcus V C A

•May 18, 2022

This course is good in general. But some parts, like the Lagrange Multipliers, needed better explanation and more exercise before testing. I also missed more supplementary material.

By Kalpak S

•Mar 8, 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.

By xiao f

•Apr 22, 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.

By Florian C

•May 28, 2021

The course starts off somewhat too basic for my taste but still gives a great intuition for some off the fundamental concepts underlying gradient descent and machine learning.

By 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.

By Prathamesh P C

•Jun 25, 2020

They should explain concepts in detail. They just explained really tough concepts in 5 min and gave much much harder assignments which was really frustrating at many times.