返回到 Mathematics for Machine Learning: Multivariate Calculus

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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....

DP

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.

SS

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.

筛选依据：

创建者 minsq n

•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!!

创建者 Fadillah A M

•Aug 01, 2020

This is a great course! The materials covered in this course are explained very very simply and profoundly. However, several terms are not explained in detail.

创建者 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!

创建者 Andi S R

•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.

创建者 Ashish P

•Oct 15, 2020

Amazing course! I wonder how instructors can teach so much in a very short span of time. Concise and succinct! Thank you so much Coursera. I am so happy.

创建者 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!

创建者 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.

创建者 Khandakar A H

•Jul 02, 2019

This course was amazing for me . I've learnt both the use of calculus and coding with it . now I can better understand mathematical tools and it's use.

创建者 Tse-Yu L

•Mar 12, 2018

Review course for multivariate calculus and basic optimization method used for curve fitting. Suggest to provide more hint for programming assignment.

创建者 Arunish S

•Jul 27, 2019

The best calculus lectures so far. It really helps you o dive into the concepts of calculus used in machine learning and covers every core concepts .

创建者 Dr. S R J K

•Jul 18, 2020

A very good course to understand the role of Calculus in various fields. Concepts were explained in a precise manner with interesting illustrations.

创建者 Sailesh N

•Oct 16, 2019

I had very good experience learning this course. I have learnt the real life application of calculus. The explanation of each videos was very good.

创建者 Yana K

•Apr 11, 2019

Great course, very good introduction into calculus for ML. Great explanation of neural networks and math used for them. A bit tricky last 2 weeks.

创建者 Saurav B

•Nov 25, 2018

An intuitive introduction to multivariate calculus and its applications in Machine Learning - the perfect course for a budding computer scientist.

创建者 Max B

•Apr 20, 2020

I benefitted a lot from this course. I liked the fast pace and feel that I understand the math behind the machine learning algorithms better now.

创建者 Mohamed R

•Sep 10, 2018

one of the best courses I have ever had.

thanks to instractors and Imperial College London

thanks so much for that specilization it helped me alot

创建者 Aaron B

•Jun 10, 2018

Excellent class! I feel like I finally understand calculus after all the rote memorization I had in my high school and college calculus courses.

创建者 Shaiman S

•Apr 28, 2020

Mr. Sam Cooer and Mr. David dye made things very simple to learn. However, inclusion of some more numerical methods can make this course ideal!

创建者 BALAJI R

•Jun 10, 2019

That's some excellent course to take for! Awesome explanations for the concepts and I strongly recommend khan academy for further explanations.

创建者 Mark J T

•Jan 25, 2020

The course is a very concise and excellent introduction to the calculus necessary. It answers a lot of questions with respect to optimization.

创建者 Phạm N M H

•May 23, 2019

This is one of three course in Mathematics for ML, it'll give you intuition for understand the true meaning of ML/DL/AI , it's all about math

创建者 Amartya M

•Aug 30, 2020

Quite a good overview int the concepts. Lucid explanation and good quizzes. Would recommend Khan Academy Multivariate calculus on top of it

创建者 Julio G

•Apr 13, 2020

Great introduction into optimisation. Looking forward to continuing with the 3rd course. Thanks Imperial College for having this available.

创建者 Roshan B

•Jul 23, 2019

An excellent review course for those who had not used calculus for a while. The derivation of the back propagation algorithm was excellent!

创建者 Gopalan O

•Aug 18, 2019

Excellent course on multivariate calculus and application of calculus in Machine Learning. Loved the assignments and the programming ones.

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