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About Advanced Deep Learning Questions - ChatGPT
Batch normalization is a technique that normalizes inputs to each layer during training to improve training neural networks by reducing internal covariate shift and helping faster convergence. Mini-batch gradient descent updates model parameters using the gradient computed on a small batch of examples, providing a balance between SGD and batch gradient descent. Common activation functions include ReLU, sigmoid, tanh, and softmax. Overfitting occurs when a model memorizes training data instead of learning patterns, and can be addressed using regularization, early stopping, dropout, and more data.
Detailed Information
| Author: | ['Lily Lauren'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 13 |
| Language: | English |
| Format: | |
| Price: | FREE |
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