Chevron Left
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: 4,864
Рецензии: 870

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

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.

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.

Фильтр по:

826–850 из 873 отзывов о курсе Mathematics for Machine Learning: Multivariate Calculus

автор: Marcin

12 авг. 2018 г.

It's one of the toughest things that I've done in my life. The content is really interesting and applicable, but at times you might get stuck with quizzes or assignments because there is not enough guidance given. All in all, I'd recommend this course to everyone working in analytics.

автор: Sam C

17 апр. 2018 г.

A quick short introduction to multivariate calculus and few machine learning techniques, but without much detail mathematical proofs for some ideas. It's a maybe good introductory course for beginners of calculus. Not recommended for learns who seek for details of ideas.

автор: Kirill N

16 авг. 2020 г.

Weeks 1-3 (4) were pretty nice; weeks 5 and 6 were terrible. The harder the topics, the less explanation was given, the pacing by the end was atrocious and course delves into statistical topics while it probably could've dedicated these weeks to other relevant topics.

автор: Vĩnh K P

22 сент. 2021 г.

The last 2 modules have very promising content, yet the instructor did not do well enough. I found myself totally lost in the confusing explanation of David, although I've already have experience in Multivar Calc and take this course just as a refresher.

автор: Yi Z

3 авг. 2018 г.

Such a easy course, if you totally a novice in multi-variables calculus, you could take this course, Whereas, if you are familiar with calculus, it will be quite easy for you.

I hope more programming assignment about Machine Learning

автор: Rob E

11 авг. 2020 г.

The instructor for this course actually tried to explain the concepts, unlike the other two courses in this specialization. However, no one is available to answer questions.

автор: Shivam K

30 июня 2020 г.

I feel that the course was too fast paced. I had to constantly refer to many other website like khan academy and 3b1b. The course skipped many details and lacked intuition.

автор: pranshu s

17 окт. 2020 г.

You will get some intuition of mathematics used in Machine Learning as well as there will be less fear in doing ML courses if you would complete this course.

автор: Alfred S

13 янв. 2019 г.

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.

автор: Kumar S

9 авг. 2020 г.

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.

автор: TirupathiRao p

21 мая 2020 г.

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

автор: MAYANK G

4 июля 2018 г.

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

автор: Kamoliddin N

7 дек. 2019 г.

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

автор: Lieu Z H

18 нояб. 2019 г.

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

автор: Saurabh M

29 сент. 2020 г.

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

автор: Lee j

23 мая 2019 г.

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

автор: Erwin M

28 апр. 2021 г.

The basics is explained so light, that you wonder if it is of any use.

автор: Akeel A

29 авг. 2020 г.

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

автор: Gurrapu N

7 апр. 2020 г.

Strong disconnect between teaching videos and assignments.

автор: joseph k

13 апр. 2020 г.

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

автор: Alkis G

14 июля 2019 г.

There is a decent space for course improvement.

автор: prudhvi

23 июня 2019 г.

week 6 content is not clear at least for me .

автор: Ahmad A

22 февр. 2021 г.

Too many Assignments and Quizzes to pass

автор: Yusuf T

28 июля 2021 г.

Need to focus more on the details.

автор: สิทธิพร แ

12 июня 2020 г.

Week 5 and 6 Lecture quite poor