<ul><li>The activation function called 'No Activation' simply outputs the given value without any processing.</li><li>The Sigmoid activation function is used for binary classification tasks, providing outputs in the range of [0,1].</li><li>The Tanh activation function is used for cases where three output cases are required: negative, neutral, and positive, with a range of [-1,1].</li><li>The Rectified Linear Unit (ReLU) activation function returns the input value for positive inputs, and 0 for negative inputs, making it popular in neural networks.</li><li>The Leaky ReLU activation function is an improved version of ReLU, allowing small non-zero outputs for negative inputs.</li><li>The Softmax activation function is used for multiclass classification, producing a probability distribution over multiple classes.</li></ul>

Activation Functions in NN

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