Voltar para Mathematics for Machine Learning: Multivariate Calculus

4.7

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383 avaliações

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.

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por João C L S

•Apr 17, 2019

I liked the course specially because I finally understood Backpropagation, an old frustration from Andrew Ng's Machine Learning course. It covers the main topics for Mathematics for Machine Learning as promised. Two weak points: (1) the Newton-Raphson convergence problems, superficially covered in the lectures, but has a challenging test, no forum support, no other source indicated for helping us. (2) The forum is abandoned. I've set two problems, one of them about an error in a lecture and the second about the problem with Newton-Raphson lecture. No responses from the lecturers or mentors.

por Benjamin F

•Nov 01, 2019

Relevant content. Great instructions. Likable instructors. Very bad coding assignments.

por Ong J R

•Jul 23, 2018

Course videos and quizzes are good and content is clearly explained. However, too many concepts are covered with too little depth. For example least squares and non-linear least squares involve fundamental concepts that should be covered and alone, would at least 2 weeks to teach. Lagrange multipliers and Taylor series are barely introduced with very little mathematical derivation involved. I had the impression that I would learn more mathematical theory than machine learning in this course, it didn't turn out to be so.

por Carsten H

•Mar 31, 2018

Too many derivatives of pointless functions.

por Idris R

•Oct 28, 2019

Fun and challenging course! It's priceless to learn all the math behind neural networks and other machine learning algorithms without having to learn all of calculus and all of linear algebra. Those are large fields and having the material presented in a way that focuses on the most relevant pieces is hugely valuable.

por Lay K L

•Dec 27, 2019

The focus on building intuition about why were are using a certain technique to approach a certain problem, instead of grinding on endless calculus problems in a traditional undergraduate class is very helpful for learning quickly - the class covers a lot of material in a short time.

por Kuldeep J

•Aug 25, 2019

All the mathematical constructs and deep calculus was explained in a very intuitively with the help of visually rich animations. It seems the course content creators have spent good amount of effort in creating animations for every little useful thing, kudos to them.

por Bryan S

•Feb 19, 2019

I began this course without any knowledge of calculus and I was still able to get along decently well. I did a bit of supplementary work using Khan Academy but that was more to ingrain the calculus knowledge gained (product rule, chain rule, etc) within this course .

por Mohammad O B S

•Nov 09, 2019

This course is perfect for those who prefer to understand the intuition behind multivariate calculus, visualize the power of gradients in optimizing functions, and apply calculus to machine learning with robust understanding of underlying mathematical concepts.

por Avinash

•Feb 17, 2019

This course delivers its promise it is very crisp and concise. After completing this course I just feel I have remembered all vector calculus taken in my engineering maths (which is almost 8 years back) :)

I highly recommend this course to getting started ML/DL.

por 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

por 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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por 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.

por 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.

por 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.

por 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!

por 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!

por 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.

por 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

por 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.

por 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.

por 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.

por 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

por 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.

por 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.