@SinarJourney
This channel is golden, i really like how you explain the concepts until execution to practical coding.
@justin.c249
so far this is the best explanation on bagging technique I found on Youtube! Great Work
@paulkornreich9806
This exercise was a challenge. Thank you. By just taking pure z of the set, some outliers were missed. Basically, all the outliers were the 0s for blood pressure and cholesterol. With those eliminated, I got significantly higher scores than the solution. All bagged models gave a similar 86% accuracy. The biggest jump from non-bagged model to bagged model was the Decision Tree which went from 79% accuracy without bagging to 86% with bagging. Also, I did the exercise several months after this video (was posted - not sure when it was made), so the libraries (especially SVC) may have improved (in their defaults).
@jasonwang-wg8wu
this was nice and straightforward, and the quip about "copy and paste" was hilarious
@ritvijmishra4727
Thank you so much sir for this ML playlist. Your explanations are simple, exact, and extremely easy to follow. The method that you use of first familiarizing us with theory, then with a practical example and then an exercise is really effective. Looking forward to more of such videos in your ML series. Thanks once again, sir.
@danialsoleimany259
The most helpful video for bagging , thank you
@Koome777
My results of the exercise: svm standalone 0.8, after bagging 0.8, Decision Tree standalone 0.65, after bagging 0.79. Bagging helps improve accuracy and reduce overfitting, especially in models that have high variance. Mostly used for unstable models like Decision Trees
@siddheshmhatre2811
One of the most underrated playlists for ML . I wish lots of student will join ❤
@shafinhossain3810
Thanks a lot for providing very necessary and important contents!
@khanshian2077
Your tutorial series are teaching me a lot Sir. These are such well organized. You have made these so easier to learn and understand. Hats off to your hard work. A blind follower of you, Sir. Loads of love. <3
@elahe4737
That was clearly describe what is the bagging method, I wish you had a video about Boosting as well
@ankitjhajhria7443
why are we fitting our model on X,y then what is the use of x_train and y_train and no use of scaling also if we are trainning our model on original X and y ?
@aniketmlk6
Thanks a lot for your awesome series!
@RekT_26
great video, best video on the topic
@rahulranjan8682
Thumbs up! You cannot learn swimming by seeing. Who takes the pain of providing excercise. When i was trying to learn in the beginning this was what i wanted. But atleast good some1 is providing it now.
@dataguy7013
Best explanation, EVER!!
@nachiketgalande8125
Thankyou SIR! for this amazing playlist on machine learning
@vikassengupta8427
Sir, i clicked the link without trying the exercise, my laptop is coughing right now, what can i do sir, nowww😢😢😢
@1itech-Learn
Thank you so much sir for this ML playlist
@codebasics