4. Aug. 2020
I felt that I took the best descition in taking this course, because the professors took this course with atmost clarity and made even the difficult concepts understand easily.\n\nThank you Professors
26. Nov. 2020
Thanks Coursera and Duke University for this course. It is very insightful to get understood the basics of ML and applied ML in numerous fields. It really made me to move ahead with ML domain.
von pritam D•
31. Mai 2021
von Viktor B•
24. Juni 2021
It's an introductory course, so what you'll get is an intruductiory overview. During the lecture videos, you'll have to take some things for granted. Some of them are explained later, some are not. What I do mind is that there is no interaction between the course staff (lectures or assistants) and course participants. So some of your questions will be left unanswered, and on some you'll get questionable answers. More and more I find this to be the general problem with Coursera. You have few graded quizes and few lab exercises. So in my opinion, the course is not worth paying extra money for the certificate.
von Evren O•
22. Juli 2021
I enjoyed Lawrence Carin's explanations a lot but the overall experience was not great I'm afraid. It felt like it did not come together properly. The order of lectures and assignments felt wrong. The Python level of competence was too high for this course and support (via forums) was non-existent. I don't regret finishing the course but I would not recommend it to my friends.
von Grace F E P•
28. Apr. 2021
The lectures were great and very easy to follow! However, I found that the assessments were too easy as they comprised solely of multiple choice questions, maybe including hands on coding assessments fo contribute to our final grade would have made me feel more confident that I've grasped what was supposed to be taught to me each week.
von Vaibhav B•
2. Mai 2021
Modules need a bit of synchronization.
Please spend some more time explaining gradient descent.
If possible, explain using a board where we could have things simultaneously.
Also, request to have a course on machine vision using CNN etc.
von Aditya Y•
30. Apr. 2021
This course is good for just theoretical understanding of the subject. But for practical implementation it is too hard to do.
von ANETTE A•
10. Juni 2021
Thank You team Coursera and Teachers from Duke University for helping me to understan dthe basics of machine learning..
von mehrshad b•
23. Apr. 2021
More examples should be provided for each course, and the content needs to be more simplified.
von Yusuf J•
23. Mai 2020
The theory is well explained but you guys should update the coding parts to TensorFlow 2.
von FARRUKH G•
11. Jan. 2022
The course requires more detailed intuitive approach towards material preparation
von Karnati S A•
8. Juni 2021
some concepts were difficult to understand and not explained very well
von anand s•
20. Juni 2022
just a basic overview of the methods. not much worth the time
von Laura S•
17. Mai 2021
I could not even understand the introduction class
von Sarah G•
1. Sep. 2019
Pretty good introduction to Machine Learning!
von MITHILESH K R•
13. Sep. 2020
von Liona L•
28. Okt. 2021
The concept is taught ok, but it's not great on hands-on learning.
von Luis S•
26. Jan. 2022
Topics are explained in a random and ilogical fashion. For example, they teach CNNs before gradient descent or the basics for training a model (like training splits or criteria to evaluate a model). Lack of order, toghether with confusing figures and poor metaphors, make impossible to properly understand any concept, and that can be seen in the discussion forums. In addition, there are gross conceptual errors, like suggesting that problems with non-linear solutions requiere NNs and can't be solved with linear regression algorithms. In fact, the whole course is centered in neural networks despite being presented as an introduction to ML and sells the idea that somehow NNs are the ideal solution to any non-trivial problem. This course is in shocking contrast with some other excelent courses that can be found in this pplatform, like the ones from Standford or Michigan.
von Jose V A S•
6. Nov. 2021
muy poco ejemplos prácticos que se puedan seguir la momento de la explicación, hablan de una manera muy general pero no no dan ejemplos explícitos de su uso. no muestran como se transforma una palabra en un vector, el único ejemplo con el que se logra entender lo que esta realizando es el ejemplo inicial de los triángulos desplazándose sobre los filtros y las imágenes, en el resto de temática nunca aterrizan sus ejemplos
von Fabián G F•
8. Nov. 2021
From my point of view as student who completed all weeks:
-The forum is totally dead. Nobody answers the questions since months. No support.
-You will not have a feedback of the assignments that you do.
-Confusing explanations. The order is not the correct
-Very theoretical and few practice.
You will need to search on internet other explanatioins to understand some parts. Hope standford course is better.
von Giorgi T•
8. Juli 2021
Very poor and low quality explanations.. lecturer starts the very first video mentioning about neural networks, convolutional networks, deep learning.. etc.. dropping a huge number of buzzwords and just following the script of the lecture, without realising, that he hasn't even said: WHAT EXACTLY Machine Learning is..
Very vague and obscure.
von Artyom L•
19. Apr. 2021
Question 1 Quiz 1: Why is machine learning exciting? Really? Glad that's a free demo course, otherwise would've been a waste
Can't speed up the video. Speaker's too slow
von Divyen M B•
19. Apr. 2021
Do not like how I cannot unenroll myself even if I see how this course is something I am not being able to manage.
von Shivani J•
27. Apr. 2021
I dont have the requird skills for the course and now I am unable to unenroll from the course.
von Mike C•
30. Apr. 2021
Very advanced for an introductory course in my opinion
von Abdul N B•
20. Apr. 2021
Please cancel this course. I want to opt out of it