Once we have created a model, we need to feed data into it in order to train it. There are two main ways to feed data into a Keras model:
- Using the fit method
- Using the predict method
The fit method is used to train the model on a dataset. The predict method is used to make predictions on a dataset.
Using the fit method
The fit method takes two arguments: the training data and the training labels. The training data is a NumPy array, and the training labels are a NumPy array.
Here is an example of how to use the fit method to train a model:
model.fit(x_train, y_train, epochs=10)
This code will train the model on the x_train data and the y_train labels for 10 epochs.
Using the predict method
Now, let's see how to feed data to the model. We can do this by using the predict method.
predictions = model.predict(x_test)
The predict method returns a NumPy array containing the predictions for the test data. The predictions are probabilities, so we can use them to classify the images.
