임페리얼 칼리지 런던의 Mathematics for Machine Learning: Multivariate Calculus 학습자 리뷰 및 피드백

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).

Very challenging course, but if you,re not afraid of numbers this is a great way to remember or "start to learn" advance and esential mathematic concepts for machine learning

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.

Really insightful course, the coding exercises are supposed to be intermediate level but are more beginner friendly. So that's a plus point if you are a beginner in Python.

Loved the course. Backpropogation section needs more elaborate explanation, where are we doing dot products, where are we doing matrix multiplications, things go confusing.

Excellent course for learners who likes self-learning. They will enjoy a deep understanding of the multivariate notions like the Hessian, Taylor series, and Regression.

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 :)

Excellent course. The material is taught in a precise, clear and intuitive manner. It would be great if a summary of the course will be given in form of some document.

Strongly agree that, this is best course ever at the beginning of Machine Learning journey. Thank you Dr. Sam and other lecturers. thank you so much Imperial College

It was way difficult compared to what I thought. Though I did not understand 100%, it gave me confidence to dig deeper if required. Thanks for this wonderful course.

One of the best courses on mathematics for machine learning. I already knew Calculus but this course reinforced and clarified many of these already learned concepts.

Excellent course! It helps understand to take the sandpit as an example for learning Jacobian, Hessian and steepest algorithm stuff. More than boring math formulas.

I really like this series so far and felt in love with instructors and the way they teach ,and i am so excited to the third and last course of this specialization.

Thank you! This was an excellent course. I think it would engage learners of any level. quality of the content, delivery, exercises and assignments were impeccable.

Great course, and i'm able to use these concepts more intuitively and confidently. The last 2 weeks were not as clear and a bit of a rush, but the rest was great!!

A great calculus introduction course that guides me into the world of machine learning, it was a great experience studying calculus with imperial college London!

This is a great course! The materials covered in this course are explained very very simply and profoundly. However, several terms are not explained in detail.

A very fast-paced course that managed to make light work of some seriously heavy maths, although it was still very challenging. Overall, it was a lot of fun!

It was a difficult topic, but it is satisfactory to understand the foundations behind the Gradient Descent algorithm. I am very satisfied with this course.

Amazing course! I wonder how instructors can teach so much in a very short span of time. Concise and succinct! Thank you so much Coursera. I am so happy.

Nice course for those want to learn machine learning. I think if there is more rigorous content such as more advanced reading materials would be better!

Excellent walk-through, good pace and good content. I've particularly enjoyed the Python notebooks experience, it really helps developing the instinct.

This course was amazing for me . I've learnt both the use of calculus and coding with it . now I can better understand mathematical tools and it's use.

Review course for multivariate calculus and basic optimization method used for curve fitting. Suggest to provide more hint for programming assignment.