Вернуться к Mathematics for Machine Learning: Multivariate Calculus

# Отзывы учащихся о курсе Mathematics for Machine Learning: Multivariate Calculus от партнера Имперский колледж Лондона

4.7
звезд
Оценки: 4,842
Рецензии: 863

## О курсе

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....

## Лучшие рецензии

SS
3 авг. 2019 г.

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 нояб. 2018 г.

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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## 701–725 из 868 отзывов о курсе Mathematics for Machine Learning: Multivariate Calculus

автор: Tai N

25 июня 2021 г.

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.

автор: Saikumar S

13 янв. 2020 г.

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.

автор: Ankit C

28 мар. 2020 г.

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

автор: sujith

16 сент. 2018 г.

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.

автор: Switt K

27 июля 2020 г.

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.

автор: George K

21 сент. 2018 г.

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.

автор: Jacqueline B

6 апр. 2020 г.

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

автор: Izzan D

29 мар. 2020 г.

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.

автор: Peiyuan C

29 сент. 2018 г.

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.

автор: Girisha D D S

26 авг. 2018 г.

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.

автор: mrinal

7 июня 2018 г.

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 .

автор: Ashish k

28 июля 2019 г.

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.

автор: Keshav B

24 июля 2020 г.

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.

автор: Kalpak S

8 мар. 2020 г.

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.

автор: Xiao F

22 апр. 2018 г.

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.

автор: Florian C

28 мая 2021 г.

T​he 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.

автор: arnaud j

23 мая 2018 г.

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.

автор: Prathamesh P C

25 июня 2020 г.

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.

автор: Andrew

7 июля 2020 г.

Practice makes about 65% of this course, 3Blue!Brown and Khan Academy are indispensable in this course too. The course is more like an overview than an in-depth study.

автор: mayank d

10 июня 2019 г.

1.Week 5 should be taken in separate module dedicated to statistics.

2.The duration of course can be increased.

3. Week 3 and week 4 can be made more detailed

автор: Dominik K

9 окт. 2019 г.

Very good course but especially while approaching the end of the course some steps are being skipped or not explained entirely which can be a bit confusing

автор: Venkatavishnu T

22 окт. 2020 г.

This course is a good refresher, bringing all the important aspects and how it can be applied for machine learning also combining with linear algebra

автор: Satpal S R

30 янв. 2019 г.

This was a great course for learning multivariate calculus required for Machine Learning. I am thankful to the creators of this awesome course.

автор: Angelo S d O

5 дек. 2018 г.

Nice refresher! Excellent instructors! Not recommended as a first Multivariate Calculus course though. I would go for MIT OpenCourseware first.

автор: Viacheslav P

23 авг. 2019 г.

Good course, but some things seem to be not well discussed and explained, I had to refer to another resources to understand what's going on.