Ensemble Method : Bagging (Bootstrap Aggregation) l Machine Learning Course in Hindi
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- čas přidán 6. 09. 2024
- Myself Shridhar Mankar an Engineer l CZcamsr l Educational Blogger l Educator l Podcaster.
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instead of referring book first we are referring your video first 😂. Thank u for this video's . You are doing a great job.
So true
Same here
Sabki kahani 5 min ki jubani 😂❤
Now I have such faith in your videos that I upvote them first and then start watching them. 😃
Mark my words, do not slow down even if the subscribers are growing gradually. That number do not represent your channel's quality. I'm a MS data science student and this was even helpful to me for basics.
Jb bhii m koyi topic pr video search krti hu to 1st apka video chahti hu if ur video is not available then I watch another person video bcz you define everything in less time and in easy way
kal mera exma hai, or aaj mai ek raat pehle ise padh raha hu, #engineeringlife, thanku bro....
Sir Amazing way of teaching.. By comparing everything to the real world.. Need more videos...
Thank You Sir for making so easy to understand Bagging Method :) Sir You deserve more than a Million Subscribers and I am sure You will reach that target one day
00:51 Ensemble Method: Bagging (Bootstrap Aggregation)
01:42 Bagging involves creating multiple datasets using random selection and sampling with replacement
02:33 Sampling with replacement allows for multiple copies of records in datasets.
03:24 Ensemble method uses multiple bootstrapped samples for training classifiers.
04:15 Combining multiple classifiers to create a stronger ensembled model
05:06 Ensemble method creates strong learner from weak learners
05:57 Ensemble method uses voting mechanism for decision making.
06:42 C-Star mechanism uses voting for majority class
Crafted by Merlin AI.
Excellent presentation. Just little bit add that if regression problem than using output of average of all model .
All videos are awesome.
N har topics proper understand ho rhe hai
I believe Random Sampling with Replacement refers to a data point being able to exist multiple times in the same dataset, and not just being present in multiple datasets. The latter is a subset of the former.
Just amazing Sir. I wish I could write down what you have just told. I mean I tried by playing pausing continue continue but its no helping. Lol.
Nonetheless, thanks a ton. God Bless!!!
Bhai me Hindi speaking nahi hoon
But I find your tutorials to be the best amongst all (be it Hindi or English).
You rock!
full abhyas
Fab work sir ... You made it very easy to understand...
wow, great tutorial simple and informative I learned a lot from you. keep it up.
Amazing teaching method
almost 21k views and just 712 likes, bahut na insaafi hai yaar, plz like and support him.
Sir ..the way of your explanation on each videos help a lot.. please keep motivating
clear and crisp. Well, bro. Keep rocking
Thank you sir ☺️
complex concept explanation in easy way, simple great!
thanks brother thanks a lot. you are so amazing . God bless you brother
Are they following same classifier algorithm (C1 to Cn) or different. Is Random Forest part of same training data set to all base learners and Boostrapping part of different training data( by taking same from 1 big training data by sample with replacement) to different classifiers?
Useful Video Sir
please add link to this series playlist so can view previous and next videos, thx
Very nicely explained...excellent
ekdum clear!!
Can u explain the machine learning for interview preparation
Thanks sir
Sir I have a doubt as you said it gives the result based on voting, what happens if voting are result are equal?
Thankyou sir !!
Sir plz explain diffrence between Ensemble of decision tree v/s ensemble of bagged tree? 🙏
beautifully explained!!! you have a new subscriber!!!
How Class 3 knows about Class 1 ? Since every data is independent from sample data how weak learner know about each other - not clear
You're a Legend!
Thanks ✨💫
Sir explanation is very good but try to speak in english so it will understand every one
I think the way he is teaching is understandable to each and every one.
khud to seekh le Pehle English !
sir do all the baggage contains equal numbet of data points i.e is d1=d2=..dn.?
Superb explanation 👍👍🙏
Please create
Video on decision tree regression
great
Helped a lot
Sirjee one doubt, when you say random sample of the data set, iska Matlab aapne random records select kie hai ya fir random independent variables ?
Initially we select random records from original data set.
Thanks
beautifully explained!!!
what is x here? Is it a sample datapoint?
Commenting algorithm ko help krne keliye
Sir you are great
So what is the difference between bagging and boosting?
Superb....🙏🙏🙏👌👌
thank you so much
Sir machine learning ke coding in python ke vedio bana dijiya
helpful
sir please explain what is pruning
Love you sir
are random features considered or all features are considered for random datasets?
Well explained
what is classifier
Kya isme curse of dimensionality create hota hai ?
thank you
pls share the book u use to learn machine learning
Thank u.
Greate Sir!
Well explain
Bohot khoob
In Bootstrap, columns are resampled or rows are resampled?
love u sir g...
Sir can you teach weka tool
Thsnks
nice ! But why it is called bagging?
Sir...is sample size equal for all di's?
Sir Aap Notes Bhi share krte jao na
It is same as random forest or not ?
Real world example sir ek bata do jahan par ham bootstrap aggregation use karta hai
behtreen zbardast
"exam nasdeek Aa rahi h".... Exam Kal h - _-
haan ok
his recorder device says may i go to toilet plz sir ?
👌
What is c1 c3...?
different classifier
Sir I'm having doubts in machine learning can I contact through mail or WhatsApp?
rohit sharma
0:04 nahi dekha bhai pichla video . Hamlog sirf specific content search karte hai youtube pe or jiska thumbnail acha lage usko touch karte hai. To kehne ki baat ye hai ki jo bhi topic sikha rahe ho uske liye pichla video pehle dekhne mt bolo jo kuch bhi hai 5 min mai samjavo. Issliye 5 min channel ka nam hai nhito sare video dekhne ko 1 ghanta jayega 😢😢😢
Sir mjhe apki kisi b lecture ki smjh nahi ati.ap hathon k ishary bht ziada krty hen or apki example ki b smjh nahi ati sorry to say thorha slow bola kren bht tez bolty hen ap. Plz improve these things
Play speed ko slow bhi kar sakte ho
Worst explanation
thank you sir!!
thanks
Thank u sir
Thnx sir😊