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What is Normalization and Activation Functions Explained about?
The document discusses various normalization techniques such as Layer Normalization, Batch Normalization, Instance Normalization, and Group Normalization, each with distinct approaches to stabilizing activations in neural networks. It also covers activation functions including Sigmoid, ReLU, and GELU, detailing their pros, cons, and appropriate use cases, particularly in the context of binary classification and modern architectures. Additionally, it provides common exam questions related to these topics, em
- Author
- Sara Zara
- Language
- EN