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What is the keyword used in
model.compile() function to represent
accuracy?
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Answer 1

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Answer 2

In the model.compile() function in TensorFlow 2, the keyword argument for representing the metric for accuracy is 'accuracy'. This argument takes a string value that specifies the metric to be used for evaluation.

For example, the following code compiles a model with the 'accuracy' metric:

model.compile(optimizer='adam',

loss='sparse_categorical_crossentropy',

metrics=['accuracy'])

The model.compile() function is used to configure the model's learning process. It takes three important arguments:

• optimizer: This specifies the optimizer to be used for training the model. The optimizer adjusts the model's weights to minimize the loss function.
• loss: This specifies the loss function to be used. The loss function measures how well the model's predictions match the true labels.
• metrics: This is a list of metrics to be evaluated by the model during training and testing. In the example above, the 'accuracy' metric will be used to evaluate the model.

In summary, the keyword 'accuracy' is used in the model.compile() function to specify the metric for measuring the model's accuracy.

To learn more about TensorFlow from the given link.

https://brainly.in/question/26692765

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