In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects of building more ethical models.
SY
A relatively short and interesting course on data fairness and bias impacting AI models.
RU
Really great discussion of algorithms and how their designs make them susceptible to bias.
CM
An excellent reminder that the bias-variance trade-off is not the only trade-off machine learning specialists make.
DV
Really appreciate given materials, especially good reading references!
Showing: 20 of 21
Some aspects of fairness and bias discussed in the session are good. I hope there is still a scope to improve the content. The review questions to test the knowledge are tricky and make us focus on the content.
En lo personal me pareció un curso muy bueno, tal y como dice el titulo es lo que enseñan, y lo enseñan de una muy buena manera hay cosas con las que me quede con duda pero las resolveré próximamente en los foros, un punto negativo es que no todos los videos tenían subtítulos en español quera que no seria bueno ponerlos en español, fuera de lo de los subtítulos es un curso muy bueno, breve pero muy bueno.
Extraodinary course! I've learnt so much! The classes are very informative and dynamic. Didn't feel like studying but rather entertaining myself with hight quality content! Thank you so much!
Really great discussion of algorithms and how their designs make them susceptible to bias.
A relatively short and interesting course on data fairness and bias impacting AI models.
I love what you do and how you do it at learnQuest, keep doing great work
Really appreciate given materials, especially good reading references!
Muy interesante el curso, me gusto bastante
learned so much from this course
I loved it. Quite an eye opener
شكرا stc شكرا coursera.
very good course
EXcellent
great
`````
good
5/5
R
An excellent reminder that the bias-variance trade-off is not the only trade-off machine learning specialists make.
While the course content is very interesting and good, there needs to be some actual notes, beyond the video transcript available to students - the transcript is printer unfriendly. Concepts can be new and sometimes challenging if I only have video material to reference. The review questions for knowledge testing and Course graded Quizzes are often phrased in a tricky manner too.