Mathematics for Machine Learning: Multivariate Calculus に戻る

4.7

星

3,377件の評価

•

572件のレビュー

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....

Aug 04, 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.

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.

フィルター：

by Irene L

•Nov 25, 2019

very good course about the math for machine learning, they teach every detail and I was able to complete the quiz and assignment just after class and don't have to seek help on Google.

by Marvin P

•Apr 06, 2018

Just like the linear algebra one this course is absolutely awesome. The instructors provide structured insights, the assignments are well prepared. I'm amazed how much fun math can be!

by Timo K

•Apr 03, 2018

Just a great course for getting you ready to understand machine learning algorithms. The chapter on backpropagation is simply outstanding and the programming assignments are awesome!

by Laszlo C

•Nov 21, 2019

It's a very intuitive re-introduction to multivariate calculus with edifying programming assignments and quizzes. I highly recommend this course for anyone who wants to tap into ML.

by Mark C

•Jul 31, 2018

As good as the first class in the Math for ML series. Instruction was interesting. Questions were not too confusing. Clearly a lot of time was spent producing this class. Thank you.

by Arihant J

•Jul 19, 2018

Nice course. Ppl with who don't have some experience with the content may find the instruction too sparse. But for someone with a decent background its a fucking fantastic course !

by Wang Z

•Jul 02, 2018

A wonderful course. I learnt a lot after struggling to finish it. Some foundations of calculus might be needed since the lecturer goes through differntiation in a tremendous speed.

by Shailesh B

•May 11, 2020

Excellent contain and I enjoyed a lot during this course. Assignment part was very crucial because there was chance to improve our understanding by giving correct or wrong answer.

by David C

•Jul 25, 2018

I highly recommend this course.

Every Machine Learning student have to do it. Some concepts is so clearly explained that you will be able to perform better in following ML studies.

by Nagaradhika

•Jun 09, 2020

excellent teaching very good course for learners thank you so much for giving this pack of three courses . Tahnkyou coursera team, three instructors and Imperial college London

by Dawn D

•Mar 10, 2019

Really good introduction for things like regression and gradient descent. An extremely good refresher for calculus and extension from what is taught in school (in UK at least).

by Ramon M T

•Sep 19, 2019

Excellent course to understand what is behind the techniques and why not high-level functions that are used in machine learning programming. Thanks for your teaching Dave, Sam

by Marina P

•Aug 28, 2019

Very practical and useful! I got an idea about what neural network is and what is inside of the regression algorithm. I enjoyed the course, although it was quite challenging.

by Rishabh A

•Jun 09, 2019

Loved the course. Backpropogation section needs more elaborate explanation, where are we doing dot products, where are we doing matrix multiplications, things go confusing.

by THIRUPATHI T

•May 21, 2020

Excellent course for learners who likes self-learning. They will enjoy a deep understanding of the multivariate notions like the Hessian, Taylor series, and Regression.

by Marwa A E K M A Z

•Nov 12, 2019

This course is really informative and builds intuition for the topics covered, I'd like to specially thank Sam for his amazing way of teaching and his visualizations :)

by Вернер А И

•Mar 17, 2018

Excellent course. The material is taught in a precise, clear and intuitive manner. It would be great if a summary of the course will be given in form of some document.

by Shammunul I

•Apr 12, 2020

One of the best courses on mathematics for machine learning. I already knew Calculus but this course reinforced and clarified many of these already learned concepts.

by Chi W

•May 17, 2018

Excellent course! It helps understand to take the sandpit as an example for learning Jacobian, Hessian and steepest algorithm stuff. More than boring math formulas.

by Akshaya P K

•Jan 03, 2019

Thank you! This was an excellent course. I think it would engage learners of any level. quality of the content, delivery, exercises and assignments were impeccable.

by Ng M M

•Apr 10, 2020

Great course, and i'm able to use these concepts more intuitively and confidently. The last 2 weeks were not as clear and a bit of a rush, but the rest was great!!

by James D

•May 16, 2020

A very fast-paced course that managed to make light work of some seriously heavy maths, although it was still very challenging. Overall, it was a lot of fun!

by Andi S

•Mar 01, 2020

It was a difficult topic, but it is satisfactory to understand the foundations behind the Gradient Descent algorithm. I am very satisfied with this course.

by 郝亚洲(Yazhou H

•Jul 17, 2018

Nice course for those want to learn machine learning. I think if there is more rigorous content such as more advanced reading materials would be better!

by Cyprien P

•Jul 08, 2020

Excellent walk-through, good pace and good content. I've particularly enjoyed the Python notebooks experience, it really helps developing the instinct.