ANN Series - 2 - The Loss Function and Cost Function

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  • Both loss functions and cost functions are central to the training and optimization of ANNs. They guide the adjustment of model parameters to improve performance. The loss function applies to a single data point, while the cost function is an aggregate measure over the entire dataset.

  • Minimizing the cost function, which involves adjusting the model's parameters, is achieved through optimization algorithms like gradient descent. The following example finds the loss function and cost function for a hypothetical dataset solving the regression problem.

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