{"p":"can-20","op":"mint","tick":"can","amt":"1000","rows":[{"df":"qa","content":[{"q":"What are activation blocks?","a":"The activation block (also known as activation function) is a processing and transformation unit used in neural networks and deep learning to handle input data. It consists of an activation function, which converts input data into output data. The activation function plays a role of nonlinear mapping in neural networks, enhancing the expressive power of the model  and allowing neural networks to learn more complex functions. Common activation functions include sigmoid, ReLU (Rectified Linear Unit), and tanh. The existence of the activation block enables neural networks to better adapt to various tasks, such as classification, regression, and so on."}]}],"pr":"7f4ad3b05b1c6dd1b127da9b1e41da473d67cf538c598b312dd0e30a2336a290"}