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Kernel Initializers in Deep Learning: How to Choose the Right One
- Kernel initializers play a crucial role in the performance of deep learning models.
- Poor weight initialization can lead to issues like vanishing or exploding gradients and slower convergence.
- Popular kernel initializers include Xavier (Glorot), He, LeCun, and Orthogonal.
- Choosing the right initializer based on the activation function is important for training stability and speed.
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