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.
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來自MATHEMATICS FOR MACHINE LEARNING: MULTIVARIATE CALCULUS的熱門評論
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.
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.
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.
Very clear and concise course material. The inputs given during the videos and the subsequent practice quiz almost force the student to carry out extra/research studies which is ideal when learning.
Excellent course!\n\nI studied multivariate calculus during engineering. I hardly understood the concepts at that time, this course helped me understand and visualize what is going behind formulas.
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 .
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.
I highly recommend this course.\n\nEvery 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.
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!
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.
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.
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 !
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.
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.
The course is still a bit young, some errors appear here and there sometimes, and some parts of it are a bit steep.\n\nOtherwise, this is a good course, focused on derivatives.
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).
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
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.
Loved the course. Backpropogation section needs more elaborate explanation, where are we doing dot products, where are we doing matrix multiplications, things go confusing.
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 :)
關於 数学在机器学习领域的应用 專項課程