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L2 norm weight penalty regularization
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This list will help you get an intuitive idea of L2 regularization for weights in deep learning.
Potential Use Cases
Mathematical foundations behind Deep Learning
Who is This For ?
People interested in knowing how Deep Learning model training works.
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1. Conceptual understanding of applying L2 penalty on weights.
Gives a visual understanding of what L2 penalty does for a simple 2-d case.
2. How is L2 regularization implemented practically?
How is L2 regularization different from its conceptual understanding?
3. What does L2 penalty actually does to the weights in comparison to unregularized cost function?
How to mathematically associate the weights learnt using regularized cost function with weights learnt for unregularized cost function?
4. [Example] A case of L2 regularization for Linear regression.
How L2 penalty applied to Linear regression problem help to handle strong multicollinearity?
5. What does it mean to penalize weights using norm ?
How does penalizing weights lead to regularization?
Why penalty is applied only to weight matrices and not biases?
6. What is regularization?
What is regularization?
What is the need of preventing model from overfitting?