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

It great course but the numpy will be new for some one who don't know to code.

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

Good course and gives a good understanding!

Notebook test case sometimes crashes

You are perfect Platform Coursera

Nice for review.

Good Professor !

The material was great and very informative, and intuitive. That said, there were a few times when 1) the lab didn't align with the learnings - multiple variables were used in labs before described in later lectures. 2) The final quiz asked questions about using Newton's method approximation recursive formula, but the language used was very different than how the concept was taught in previous lessons. If mentors/contributors can look through the lessons/labs/quiz and ensure there is fluidity, that would be very helpful. Thank you!

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However the Python is horribly outdated, back at 3.8; which will sunset in a year and a few months.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

a little bit overwhelming. I still dont feel like I understand everything. I wish it was more interactive. especially with writing codes and mathematics. I was stuck with many questions and felt demotivated.

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.

better than linear algebra course.

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