python-kerasHow can I use Python and Keras to build a convolutional neural network?

To build a convolutional neural network (CNN) with Python and Keras, you need to follow a few steps:

1. Import the necessary libraries:

import keras
from keras.layers import Conv2D, MaxPooling2D, Flatten, Dense

2. Create the model:

model = keras.models.Sequential()

3. Add convolutional layers:

model.add(Conv2D(32, (3, 3), activation='relu', input_shape=(64, 64, 3)))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(64, (3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

4. Add flattening layer:

model.add(Flatten())

5. Add a fully connected layer:

model.add(Dense(128, activation='relu'))

6. Add output layer:

model.add(Dense(1, activation='sigmoid'))

7. Compile the model:

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

For further information, please refer to the following links:

• Keras Documentation
• Building a Convolutional Neural Network (CNN) in Keras
• Convolutional Neural Network (CNN) Tutorial

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