ModelCheckpoint is a callback function in the Keras library for Python that allows us to save the model weights during training. It is used to monitor the performance of the model at different epochs and save the best set of weights based on a specified metric, such as validation loss or accuracy. By using ModelCheckpoint, we can ensure that we have access to the best model weights achieved during training and use them for future predictions or to continue training from where we left off.
Python ModelCheckpoint - 34 examples found. These are the top rated real world Python examples of keras.callbacks.ModelCheckpoint extracted from open source projects. You can rate examples to help us improve the quality of examples.