Good Professor !

kind of tuff

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However the Python is horribly outdated, back at 3.8; which will sunset in a year and a few months.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

El curso es para personas con python avanzado, pero en la información entregada decía que no se necesitaba saber de forma experto python. Se recomienda ser mas especifico.

Videos: great, easy to follow

Labs: not so great

week 3 was hard for me

too easy

Some more details and maybe another week of new material would be good. Some of it was a rehash of the ML specialization coursera course. Explain also why integrals are not needed. didn't teach taylor series or other concepts that come up later in the probability course that are calculus related

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 course material and delivery felt confusing, disorienting at times. I'll have to look at other resources to better understand the topics.

better than linear algebra course.

The linear algebra course was too good and this is exactly the opposite of it. I have no problem with the theory, the explanation was beautiful but when it comes to lab my first week graded lab file somehow got corrupted and it does not give me my grade. I'm disappointed with the graded labs; we cannot reset all the changes that we have made to square one again.

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

very bad learning experience