The `tensorflow.keras.models.Sequential.fit` function in Python is used to train a deep learning model using a Sequential model architecture. This function takes in the training data, labels, and other optional parameters such as batch size, number of epochs, and validation data, among others. It iteratively optimizes the model's weights based on the given data and labels, minimizing the defined loss function. The function returns a `History` object that contains information such as loss and accuracy values for each epoch, allowing for analysis and evaluation of the training process.
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