Non-linearity
Non-linearity refers to the property of a system or a model where the output is not directly proportional to the input. In data science and artificial intelligence, non-linearity is a crucial concept as many real-world phenomena exhibit non-linear behavior. Non-linear models are used to capture complex relationships between variables that cannot be explained by linear models. Non-linear models can be used in various applications such as image and speech recognition, natural language processing, and predictive modeling. Non-linearity can be introduced in a model by using non-linear activation functions such as sigmoid, ReLU, and tanh in neural networks. Non-linear models can also be created by using decision trees, support vector machines, and kernel methods.
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