Backpropagation in Neural Networks - EXPLAINED!
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- κ²μμΌ 2024. 04. 27.
- Greetings fellow learners! This is the 2nd video in a playlist of videos where are are going to talk about the fundamentals of building neural networks! Here, we cover back propagation
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If you think I deserve it, please consider giving this video a like as it would help tremendously. Thank you!
sir, please make a playlist for graph neural network(GCN,GAT etc)πππ
There is NO VIDEO on the KRplus about training mamba s4 from scratch. Can You do one, please? I belive it will be GOAT in terms of views and new subs.
Quiz:
#1: B
#2: C
#3: B
I hope :D
Haha. Nice. You answered Quizzes 1 and 2 correctly. But for quiz 3, the "negative gradient of loss wrt parameters" provides the direction along which we want to update the parameters. So the answer to Quiz 3 should be A. I try to explain this at 7:34 in the video. Hope this makes sense :)
B, C, B? Fantastic video btw, perfect for people like me with a destroyed attention spanβ¦
Thanks so much for the compliments! You answered Quizzes 1 and 2 correctly. But for quiz 3, the "negative gradient of loss wrt parameters" provides the direction along which we want to update the parameters.So the answer to Quiz 3 should be A. I try to explain this at 7:34 in the video. Hope this makes sense
For quiz 1 : B. Because neural networks are in supervised learning so we trained it with labelled data?
B
Quiz 1 answer is indeed B. How about the other 2 Quizzes ? :)
Good video, but you need to get back to digging deeper into transformers...
B
Good job! Quiz 1 answer is indeed B. How about the other 2 quizzes? :)