can't believe a professor from IIT can explain in such a bad manner, concepts of the prof. is itself not clear, at least try not to dissipate wrong information to the students there are many subtle mistakes that can shatter the whole concept of naive Bayes for the students who are learning the concept for the first time, one of many such mistakes is at 16:08 where she is saying the probability of play = yes given outlook = sunny, which is totally wrong rather it should be probability of outlook = sunny given play = yes.
worst proff. No effort to make students understand
tere bas ki baat nahi hain AI/ML tu kuchh aur karle
she just fulfilling her duty with no interest, anyone who is listening first time can't understand.
can't believe a professor from IIT can explain in such a bad manner, concepts of the prof. is itself not clear, at least try not to dissipate wrong information to the students
there are many subtle mistakes that can shatter the whole concept of naive Bayes for the students who are learning the concept for the first time, one of many such mistakes is at 16:08 where she is saying the probability of play = yes given outlook = sunny, which is totally wrong rather it should be probability of outlook = sunny given play = yes.
why dont you create a course I will take it..
being knowledgeable does not make someone a good teacher
Don't waste your time by watching full video lecture. Just move on
Thank you so much for the great explanation .
Thank you very much for your efforts. very good explanation.
Here it says that R = # of possible values of yk. Then what about M, is there any formula to find M?????
Thank You Mam
example is taken by table 3.2
Did u gave the certification exam ??
mam u r explaining in an efficent and advanced way thank you for this