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"CODE LINK"-https://colab.research.google.com/drive/1kAp9Nzb-HsVcWpnzJN83Jw1kFpSBfGeZ?usp=sharing
In this video, we dive deep into weight initialization techniques in neural networks, focusing on Xavier (Glorot) and He initialization. These methods are crucial for training deep neural networks efficiently by preventing issues like vanishing or exploding gradients.
📌 Topics Covered:
✅ Xavier/Glorot Initialization (for sigmoid/tanh activations)
✅ He Initialization (for ReLU/Leaky ReLU activations)
✅ Mathematical intuition behind these methods
✅ How to implement them in PyTorch
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