Ensemble (Boosting, Bagging, and Stacking) in Machine Learning: Easy Explanation for Data Scientists
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- เผยแพร่เมื่อ 28 มิ.ย. 2024
- Questions about Ensemble Methods frequently appear in data science interviews. In this video, I’ll go over various examples of ensemble learning, the advantages of boosting and bagging, how to explain stacking, and more!
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Contents of this video:
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00:00 Introduction
00:38 Ensemble Methods
01:40 Bagging (Bootstrap Aggregation)
03:00 Example: Random Forest
03:44 Boosting
05:14 Example: Gradient-Boosted Trees
05:47 Bagging vs. Boosting
06:40 Stacking
07:08 Two-Level Ensemble
07:44 Pros and Cons
I wish all professors explain it just like you do, well done!!
Simplest explanation I've seen for boosting. Thank you!
Your videos are always straight to the point, loving them all :)
fantastic summary, thanks for making it short and to the point!
Well explained. Thank you!
I find the video helpful. Thank you so much for the content!
thanks, tha's exactly what i was looking for, great video
Great explanation.
Great video Emma! How would we choose what the meta model is and can we also use it as individual classifier? Thanks 🙏
Informative video, thanks for sharing your knowledge.
My pleasure, Muhammad! Thanks for watching. 😊
Great Video! Can you share the notion page (if possible) as it will be a great refresher before interviews?
Of course! I'm working on getting all notes organized and sharable in one location, will let you know as soon as they are ready! :)
Here you go! You can now download all the PDFs of my Notion pages at www.emmading.com/get-all-my-free-resources. Enjoy!
Ansamble mesos?
Many of you have asked me to share my presentation notes, and now… I have them for you! Download all the PDFs of my Notion pages at www.emmading.com/get-all-my-free-resources. Enjoy!
Nice explanation..but it would be more nice if u develop your English pronunciation bcuz u sound "a,e,o" as same
You just read the file
Dont read, explain!!
I think she can't explain, just she read that's all she can do