Good complementary course to the Multivariate Calculus course by Imperial College London. I had already taken that course so I was able to skip almost all the lectures here, and jumped straight to the assignments.

Week 3 Newton's methods contained the use of Hessian instead of gradient descent, which was covered the the ICL course, but was not explained where it came from. They also used the hybrid of Hessian and Grad Descent and the use cases for both.

Overall, if you are stuck between this course or the ICL version, go with the ICL one

I also did the calculus course of imperial college london (didn't finish the last two weeks because the course gets worse after week 4) and I have to say that I enjoyed this course much more. Things are explained very clearly and I built a very good understanding and intuition of all the concepts. One could argue that the topics covered are a bit too basic, but in the end you get a good understanding of how optimization algorithms like gradient descent are working under the hood of ml-models.

Great Course! Here I find a lot of step-by-step explanations of how mathematical neural network works. A lot of examples and visualizations(a lot of animation, that can be used, as an experiment) provide a high understanding of what we using, why we using that in a certain situation, and how we can use it in practice programming neural networks. Highly Recommend!

thank you for recovering my knowledgement for math after so many years from pass my Uni

This course refresh my knowledge about calculus back in senior high school and even it makes me understand better about calculus and apply it in machine learning.

The content is fantastic, with a lot of illustrations and examples! Kudos to Luis Serrano and the DeepLearning AI team!

A good course for beginners. There are formulas that require a pen and paper to think and solve. Brilliant

Covers what is needed for ML. Provided examples, quizzes and labs are very helpful. Thank you

Those mathematical knowledge taught are very useful

There is a lot of useful knowledge

The best I have seen

So interesting!

I find the teacher engaging and the idea that it is related to machine learning, but the labs are way to focused on machine learning, and i think they are poorly designed so that it is all busy work. Little things kept bothering me, such as how the quizzes pop up and block the slide that contains the information the quiz is asking about. You have to see both the quiz and the screen it is hiding at the same time. Then, I think the labs model poor programming practices such as packing data in and out of Python dictionaries all the time, and then my job is to go through and write code to pack and unpack the Python dictionaries. It is hard for me to write code I think is stupid, expecially when doing so teaches me nothing about either calculus or machine learning.

Too simple, only the notebooks are somehow interesting

Luis Serrano is an excellent teacher, who balances explaining the topics very well but also at a level that is challenging and spurs independent thinking. The labs were very helpful & especially in learning exactly what goes on in all the layers of a neural network. Looking forward to the next course with him!

Since I got in touch with the field of ML/AI I was looking for a course to get a deep understanding of gradient descent. Finally this course made it happen and even more. My highest recommendations and thank you DeepLearning.AI for that great piece of work!

Excellent! Calculus for Machine Learning and Data Science by DeepLearning.AI definitely makes for an excellent beginner's course for appreciating the more important concepts and methods of Calculus that are used in ML and DS. Congratulations, Luis! 👏🏽🎉

good one

Too easy for exercise, but the video lession is good, focused on ML perspective

Helpfully and covered all the topics related to ML

You are perfect Platform Coursera