Weights
In the context of data science and artificial intelligence, weights refer to the numerical values assigned to the connections between neurons in a neural network. These weights determine the strength of the connection between neurons and are adjusted during the training process to optimize the performance of the network. The weights are initialized randomly and then updated using an optimization algorithm such as stochastic gradient descent. The goal is to find the optimal set of weights that minimize the error between the predicted output and the actual output. Weights can also refer to the coefficients assigned to the features in a machine learning model, which are used to make predictions based on new data.
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