Mathematics for Machine Learning

Great introduction to Multivariate Calculus with a lot of visualizations to prop up the intuition Excellent course.

excellent Review course for multivariate calculus and basic optimization method used for curve fitting.

Quality course that will leave you feeling confident in multivariate calculus and analytics.

It us good course and gave me basic understanding of multivariate calculus.

This was a great course for learning multivariate calculus required for Machine Learning.

very good introductory course to Multivariate Calculus Well the course is generally good, the only problem is that David sometimes may just skip the process and lack more explanation when performing the calculation, it's easy to lose track of what he is calculating if not reviewing the video over and over again, but anyway, the whole class is worth recommendation, thank you for your teaching, professors Very practical introduction to the subject, very well paced!

Not recommended as a first Multivariate Calculus course though.

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

I completed this course with no prior knowledge of multivariate calculus and was successful nonetheless.

I really enjoyed this course on multivariate calculus.

Very instructive, good refresher of multivariate calculus in the context of machine learning Very well teaching.

!Clear illustration on multivariate calculus.

A bit more challenging than the Linear Algebra course.

I have leant single variable calculus and linear algebra (freshman year difficulty), and this course is challenging but doable for me!

But it would be much better if the concept in linear algebra combines more with this course.

This is way better than the linear algebra course in this specialization.

Highly recommend Following on from the Linear Algebra course, this is equally excellent.

:) Great class - very informative and eye opening - even with quite a bit of linear algebra background.

It is ok Great course with a lot of math and practical examples An excellently simple explanation of concepts of linear algebra.

The course on Linear Algebra was better.

It helped me to brush up my calculus knowledge.thanks to the team Such a easy course, if you totally a novice in multi-variables calculus, you could take this course, Whereas, if you are familiar with calculus, it will be quite easy for you.I hope more programming assignment about Machine Learning the part about neural networks needs improvement (some more examples of simple networks, the explanation of the emergence of the sigmoid function).

I wish the neural network discussion went on a bit further.

I got an idea about what neural network is and what is inside of the regression algorithm.

Too fast to understand what instructors says.. but lecture contents are good 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 Professors have done a great job in explaining clearly a complex subject I think neural networks was unnecessary.

VERYGOOD Great balance between presentation and excellent exercises I highly recommend this course.Every Machine Learning student have to do it.

I recommend this course to all my friends and others interested in.

I highly recommend this course for anyone who wants to tap into ML.

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.

Efficient tutors who were able to inculcate interest in me towards finding out the roots of machine learning algorithms.

If there are more of neural network course that Imperial College can come up would be best.

one of the best courses I have ever had.thanks to instractors and Imperial College Londonthanks so much for that specilization it helped me alot Fantastic overview/refresher of multivariate calculus, with links to ML / neural nets throughout.

Excellent course, some parts in the last weekend were not so clear Good course ..but need to elaborate a little more Excelente.Muchas gracias por compartir generosamente su conocimiento.Ha sido muy grato para mí repasar temas de cálculo multivariado, álgebra lineal y optimización.Gracias COURSERA, Gracias MINTIC y Gracias a The Imperial College of London.

Thanks a lot to Imperial College :) Excelent course Brilliant course that covers so much in such a short time span.

Another great course from Imperial College London.

I highly recommend this specialization.

Some parts are confusing, and I recommend looking at Khan Academy for the lectures on Jacobians and steepest ascent, and 3Blue1Brown for feedforward neural networks.

There were a couple of instances where the content wasn't clear and I referenced Khan Academy to clarify things for myself.

I had to often refer to Khan Academy and YouTube to learn the concepts which the instructors did not provide an example for.

Awesome explanations for the concepts and I strongly recommend khan academy for further explanations.

Amazing course, everything is very well explained :) 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 The first few weeks were a great introduction to derivatives, but the further it got the more the content seemed rushed and the exercises lazy.

I wish it had more sections as in a total of 12 sections or weeks and more steps to gain a more thorough graphical understanding (and perhaps even a more mathematical/algebraic understanding however overall that's much easier for me on that front...).From a Data Science or Machine Learning perspective Week 6 (linear regression and non linear regression with chi-squared methods etc) were the most interesting.

It inspires me to pursue a MS in Data Science.

A good starter course on calculus if you want to go for Machine learning or Data Sciences.

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.

The way of teaching visually rather than theoretically keeps those that get lost in formulae like me on track.

Most of the concepts i learnt were from the quizzes rather than the videos week 6 content is not clear at least for me .

It's a very intuitive re-introduction to multivariate calculus with edifying programming assignments and quizzes.

Most of the programming assignments only required the student to fill in some easier blanks.I still do not know what the Taylor Series Chapter was about.

The most outstanding part is the programming assignments: They are designed so elegantly that you can get intuition right away once you go through them.

The first four weeks are excellently prepared and the programming assignments are almost too easy at some points.

I especially enjoyed the part on gradient descent that was part of multiple modules.

Also, the sandpit exercises are great to easily understand how gradient descent works, which is a very important concept in ML.