What are Parameters in AI?

Parameters in AI are the variables that the model learns during training. They are the internal variables that the model uses to make predictions or decisions. In a neural network, the parameters include the weights and biases of the neurons.

How are Parameters used in AI?

Parameters are used in AI to determine the output of the model for a given input. During training, the model adjusts its parameters to minimize the difference between its predictions and the actual values. This is typically done using an optimization algorithm, such as gradient descent.

The learned parameters capture the patterns and relationships in the training data, allowing the model to make predictions or decisions on new data.

What is the role of Parameters in AI?

Parameters play a crucial role in AI. They are the variables that the model learns from the data, and they determine the model's performance. The quality of the learned parameters can greatly affect the model's ability to make accurate predictions or decisions.

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