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....

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.

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.

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创建者 Narayan B

•Jun 25, 2019

good mathematics course, but the things and concepts are explained in a very abstract way. Need to think a lot on your own while solving the quizzes as the videos are not going to help. Most of the concepts i learnt were from the quizzes rather than the videos

创建者 Giuliano L P

•Apr 13, 2018

Even though in the beginning calculus seems to be confusing, because of the difficulty of the content, do not give up, I can guarantee that this course is the best way to learn calculus. The content is presented in a creative and fascinating way. Unmissable.

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创建者 Anna U

•Jan 14, 2020

An excellently simple explanation of concepts of linear algebra. Applause for lector. I really liked this course and found it very useful for those newbies in machine learning like myself. I recommend this course to all my friends and others interested in.

创建者 Aleix L M

•Nov 28, 2019

I found this course really useful and concise, straight to the concepts that are used in machine learning. The lecturers speak clearly and give very intuitive views on abstract concepts that I had trouble understanding before. I would totally recommend it.

创建者 Kurt G

•Aug 04, 2019

The course began quite straightforwardly, and became progressively more challenging. I would recommend to others that they continually practice their skills at finding partial derivatives, as that skill gets even more important as the class progresses.

创建者 Shahzad A K

•May 24, 2018

Great course! Builds up logically from a soft introduction to practical applications of multivariate calculus for data analytics. I no longer feel intimidated when I look at an expression involving higher order partial derivatives in multiple variables!

创建者 FRANCK R S

•Jun 03, 2018

A very useful introduction of the math behind Machine Learning, a must if you plan to understand the algorithms used in ML, as usual the teachers are very very talented, focus is put in the essential and comprehension comes intuitively, Great Thanks!

创建者 Christoph L

•Jan 06, 2020

A very good introductory course that is giving insightful explanations of how something is done and why. I especially enjoyed the part on gradient descent that was part of multiple modules. Very engaging instructors make learning easy and motivating.

创建者 Ashok B B

•Feb 02, 2020

Fantastic course, got to know the underlying maths behind complex ML algorithms, which was always a grey area to me, the instructors clearly explained each topic, which is a definitely a must add on skill to your journey towards Data Science career

创建者 Fabiana G

•Jul 25, 2019

It's challenging, specially about the week 4. But it's very possible to conclude successful. I just have high school and I finished the course with 100% of grade. My hint is: algebra is very important, but code can help you with this subject.

创建者 Tommy R

•Mar 26, 2020

I've always felt intimidated by maths and it stopped me from really understanding machine learning and the different algorithms used. This course does a great job of making calculus understandable and demonstrates why it is so useful for ML.

创建者 Srimat M

•Dec 10, 2019

standard short and crisp course. will do the job for what it is designed for. great explanations by mr. sam cooper and his visualization team at imperial. and mr.david also done a great job. overall worth spending funny jelly belly time.

创建者 Tash B

•Sep 05, 2018

Although difficult, this course makes sense of what is happening under the hood in training machine learning models. Instructors explain things well and the assignments gave opportunities to practice. I thoroughly enjoyed this course.

创建者 Badri A

•May 15, 2020

The thing I love about this course and the previous one, is how they make these heavy equations and stuff that we learn in school and university meaningful.

The instructors are very good, and the topic was handled perfectly. Well Done !

创建者 Jafed E

•Jul 06, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

创建者 Jonathan F

•Jul 29, 2018

Following on from the Linear Algebra course, this is equally excellent. Again, the main enjoyment comes from seeing techniques learnt at school (partial derivatives, Taylor series, Newton-Raphson, etc) actually being used in practice.

创建者 Saikat C

•Feb 14, 2020

Excellent course. It provides all the math required to understand machine learning in a deeper level with everything explained. This course connects all the necessary ideas and provide a coherent view of machine learning mathematics.

创建者 Zixuan Y

•Jan 27, 2020

I have learnt Calculus 1 before, so this course is much easier for me than the first course in the specialization. With the notebook tool, I now know how to put derivative into python. The teachers are really good. Thanks a lot ;)

创建者 Nigel H

•Apr 18, 2018

A change in staff from Imperial but the same enthusiasm; high standards of teaching mean you are going to get a lot from this course. Lots of examples and the practice quizzes really help with the consolidation. Great stuff.Thanks

创建者 Mike

•Jan 13, 2020

A great course which covers the necessary aspects in a very interesting and intuitive way. Makes really good use of graphics, rather than only pure maths, in order to give an intuitive sense of what's happening behind the magic.

创建者 zohair a b

•Jun 02, 2020

Awesome course. I've always thought of math as a burden. Never really liked it. But this course has made me fall in love with mathematics. The way the instructors taught different concepts and put them all together was amazing.

创建者 jie

•Jun 11, 2020

Excellent course. I almost forgot everything i learned at college. I never thought I could regain all these knowledge with ease (was very painful back in college) . Samuel Cooper is probably the best instructor at coursera.

创建者 Sagar L

•Mar 12, 2020

A really nice course in the series. Quite useful from the perspective of the back end mathematics of ml techniques like Neural Networks. Anyone who wants to work in this domain, would be more than satisfied with this course.

创建者 Nataliya M

•Nov 17, 2018

Despite there being some mistakes in videos, this course is a nice introduction to Multivariate Calculus with application to Machine Learning and Data Science. Assignments are fairly challenging and also very interesting!

创建者 Loay W

•Aug 01, 2019

Thanks to the simple demonstration, and the interactive learning, I feel I can interpret the math as a new

language I can read and speak with, it was an interesting and core skill to have,

as a machine learning engineer.