Learn How to compile, evaluate and predict Model in Keras, various methods and their arguments, keras loss functions, optimizers and metrics. Compile, Evaluate and Predict Model in Keras
Welcome to DataFlair Keras Tutorial series. This chapter explains how to compile, evaluate and make predictions from Model in Keras.
After defining our model and stacking the layers, we have to configure our model. We do this configuration process in the compilation phase.
Before training the model we need to compile it and define the loss function, optimizers, and metrics for prediction.
We compile the model using .compile() method.
model.compile ( optimizer, loss, metrics, loss_weights, sample_weight_mode, weighted_metrics, target_tensors)
Optimizer, loss, and metrics are the necessary arguments.
Keras provides various loss functions, optimizers, and metrics for the compilation phase.
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