python-kerasHow can I use Python with Keras to build a deep learning model?

Python with Keras can be used to build a deep learning model by following these steps:

1. Import the required libraries:

import numpy as np
from keras.models import Sequential
from keras.layers import Dense

2. Create the model:

model = Sequential()
model.add(Dense(units=64, activation='relu', input_dim=100))
model.add(Dense(units=10, activation='softmax'))

3. Compile the model:

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

4. Train the model:

model.fit(x_train, y_train, epochs=5, batch_size=32)

5. Evaluate the model:

loss_and_metrics = model.evaluate(x_test, y_test, batch_size=128)

6. Make predictions with the model:

classes = model.predict(x_test, batch_size=128)

7. Save the model:

model.save('my_model.h5')

Helpful links

• Keras Documentation
• Getting Started with Deep Learning using Keras

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