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What is Unit 2 about?

The document explains the importance of activation functions in neural networks, highlighting their role in introducing non-linearity to learn complex patterns. It details various types of activation functions such as ReLU, Sigmoid, Softmax, and Tanh, and discusses the structure and learning process of a single-layer perceptron. Additionally, it covers the components of a multi-layer perceptron and provides examples of forward and backward passes in neural network training.

Author

pardhukoneru123

Language

EN