python-kerasHow can I use Python and Keras to create a Convolutional Neural Network?

To create a Convolutional Neural Network (CNN) using Python and Keras, you need to follow these steps:

1. Import the necessary libraries:

import numpy as np
from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D, Dense, Flatten

2. Create a model and add layers:

model = Sequential()
model.add(Conv2D(filters=32, kernel_size=(3,3), activation='relu', input_shape=(28, 28, 1)))
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(Dense(10, activation='softmax'))

3. Compile the model:

model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])

4. Fit the model:

model.fit(x_train, y_train, batch_size=128, epochs=10, verbose=1, validation_data=(x_test, y_test))

5. Evaluate the model:

score = model.evaluate(x_test, y_test, verbose=0)
print('Test loss:', score[0])
print('Test accuracy:', score[1])

6. Make predictions:

predictions = model.predict(x_test)

7. Save the model:

model.save('my_model.h5')

Helpful links

• Keras Documentation
• TensorFlow Keras Guide
• Keras Convolutional Layers

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