@bolgorwheat8753
Just checked the database and I got 95,000 features after vectorization lol. Seems like I really need this one.
@MohammadMonirHossain-uo2mm
Thank you sir for tutorial.
@reanwithkimleng
Hello sir, when selection feature selection methods, what need to consider?❤
@yuvaraj2457
Hi Kevin, Great respect 4 u. Y haven't u touched unsupervised and reinforcement topics? Expecting it.
@fikiledube6745
Thank you for this insightful video. I am curious about whether there is a way to find the inputs that are most influential to the output of an ML model such as ANN. Is there a way to determine this?
@meetmeraj2000
wonderfully explained!!
@ananddeshmukh4939
the way of Superior teaching!
@rdubitsk
Aren't there ML libraries that can optimize the features? Ie by running and dropping various features and using that process to optimize features included in final model?
@evanchugh4330
Do you have any tips on how to handle datasets where there is a strong class imbalance? (ie. 95% of class A, 5% of class B?) Thanks, these videos are extremely helpful!
@Analysis317
Hey Kevin, frist of all thank you sooo much for your videos! They are amazing! I got a little question to pairwise correlation and multicolinearity. If used already pairwise correlation and deleted attribute, which are highly correlated, its also nesscary to do a Multicolinearity test? Or would it be enough to use one of them, and when yes, which you ?
@martinusgrady2380
how about LDA?
@edmkiller9117
Best one :))
@khalid11221122
2 x Speed is the best speed for all his videos, great content though.
@konstantinvyacheslavovich8217
2025 lets see what is here )
@rockroll28