Thank you for watching this video. I really appreciate it. If you liked this explaining video, I also recommend to check it out other similar videos from my channel below: 1. Compare ML Models in few clicks with PyCaret in Python - ruclips.net/video/s38AvnzwKPw/видео.html 2. Kubernetes Explained | High Level Explanation - ruclips.net/video/7yytUBC8grw/видео.html 3. Calculate TF-IDF in NLP (Simple Example) - ruclips.net/video/vZAXpvHhQow/видео.html 4. How Gradient Descent Works. Simple Explanation - ruclips.net/video/Gbz8RljxIHo/видео.html
Good example. I would suggest though making the distinction between Shapley values and the SHAP calculation more clear, the title is a little misleading.
Thanks for the explanation, I have a quick remark w.r.t. the calculation done at 00:11:03 MC1 ==> OK MC2 / MC3 and MC4 the labels (definition) and the calculations do not align.
One suggestion, since you pronounce v as w, it's a good idea to just pronounce v's as f's. "falues" is much better than "walues" f an v are so close anyway and I heard you say may f-words clearly.
Thank you for watching this video. I really appreciate it.
If you liked this explaining video, I also recommend to check it out other similar videos from my channel below:
1. Compare ML Models in few clicks with PyCaret in Python - ruclips.net/video/s38AvnzwKPw/видео.html
2. Kubernetes Explained | High Level Explanation - ruclips.net/video/7yytUBC8grw/видео.html
3. Calculate TF-IDF in NLP (Simple Example) - ruclips.net/video/vZAXpvHhQow/видео.html
4. How Gradient Descent Works. Simple Explanation - ruclips.net/video/Gbz8RljxIHo/видео.html
Good example. I would suggest though making the distinction between Shapley values and the SHAP calculation more clear, the title is a little misleading.
Great explanation! Never understood this clearly from other sources!! Well done!
If in another video, if you can show how this translates to the mathematical equation for Shapley values, it will be awesome!
Thanks for feedback, I really appreciate that you found that useful! :)
About - translate to the math. equation - good idea. I will read more about that. :)
Thanks for the explanation, I have a quick remark w.r.t. the calculation done at 00:11:03
MC1 ==> OK
MC2 / MC3 and MC4 the labels (definition) and the calculations do not align.
Clear and precise explanation! Thank you so much! Loved it!
You are welcome. Thank you for watching, appreciate!
I never see such a clear explanation on Shaley values.
Thanks for watching! :)
@@DataScienceGarage please make more video on models of XAI.
Very nice video. It would be nice if the weight you have used could be related to the original shap formula involving factorials.
Excellent video! That was very helpful, thank you!
Thanks a lot for feedback! Happy you like it :)
the is the best of the best. Many thanks for the efforts
Great explanation ❤
Thanks for the informative video!
Thanks for watching it! :)
Thanks a lot! This explanation was very helpful!
Really glad it was useful, appreciate your feedback! :)
Excellent explanation
Thank you so much
Thank you for watching! :)
Well explained!
Thanks for watching! Appreciate! :)
Thanks a lot
One suggestion, since you pronounce v as w, it's a good idea to just pronounce v's as f's. "falues" is much better than "walues" f an v are so close anyway and I heard you say may f-words clearly.
I will try, thanks! :)