I actually understand gradient descent which is awesome. I need a little bit more practice running some of the problems to be proficient and remember how to do them, but I was able to complete them for the course and I suppose in real life I can just have my code (stolen from this course) find the answers.

An excellent course indeed, although with some caveats.

I love the simplicity and the examples of the instructor. However, sometimes the materials needed to be more complex and exciting to watch. I definitely recommend this course to absolute beginners in calculus or someone who needs a refresher.

We had a great time learning this course. We really had some good sessions with friends while learnin this. We found about new concepts. Thanks

Easy to follow for beginners. Concepts are well explained. I wish the Newtonian method had been explained in more details though.

The last programming assignment has some problems. If you touch the optional part, you get 0.

Knowledge very useful, however as benniger at phyton, programing task are quite hard

It was so hard and challenging. I've nearly cried and somehow i passed. Thanks :")

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

Labs could have been more difficult. Otherwise a good course for beginners.

Videos and explanations are great, but labs are rough.

Helpfully and covered all the topics related to ML

Notebook test case sometimes crashes

You are perfect Platform Coursera

Nice for review.

Good Professor !

Much time spent on Python in the labs that did not result in learning Python.

The labs make it clear that Python is VERY important, but I suggest a separate Python course to be taken first (even before the linear algebra material). Even making it into a four-course specialization is a far better use of one's time than struggling with labs that only8 illustrate, not teach, this critical tool.

Good content giving insight to the mathematical foundations of Machine Learning.

However the Python is horribly outdated, back at 3.8; which will sunset in a year and a few months.

Some of the examples are not PEP 8 compliant.

That aside it is good to really understand from where the machinations of neural networks derive.

Useful for beginners and fundamental concepts. Before starting the course I thought that the course will be helpful in professional journey but I found out that the basic concepts are discussed.

Videos: great, easy to follow

Labs: not so great

too easy

Not possible without knowing Python 3 already. Went over easy topics too slowly and harder topics too quickly. Barely talking about ML so I'm still not sure how much of this relate.

the single start is definitely more than this course deserves, the specialization should be Titled Math for elementary school or for Kids. the explanation is soo naive and topics are not well covered! please Do NOT waste your TIME going through This course as the overall gain is almost ~0.000001

this is defenitly not helping beginners , topics are not covered in an easy way , labs are a complete nightmare , defenitly made me hate machine learning , not help me understand it

Cancel lab please, It's too complicated and has a lot of unclear questions