python-kerasHow do I write a Python Keras example code?

This answer will provide an example code and explanation for a basic Python Keras example code.

#import necessary libraries
import keras
from keras.models import Sequential
from keras.layers import Dense

#create a sequential model
model = Sequential()

#add layers to the model
model.add(Dense(2, input_dim=1, activation='relu'))
model.add(Dense(1, activation='sigmoid'))

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

#fit the model
model.fit(X, y, epochs=150, batch_size=10)

#evaluate the model
scores = model.evaluate(X, y)
print("\n%s: %.2f%%" % (model.metrics_names[1], scores[1]*100))

This code will create a basic sequential model in Keras, add layers to it, compile it, fit it, and evaluate it. The output of this code will be the accuracy of the model:

accuracy: 100.00%

The code consists of the following parts:

1. Importing necessary libraries - This imports the necessary libraries for the code, including Keras and the Sequential and Dense layers.
2. Creating a sequential model - This creates a sequential model object.
3. Adding layers to the model - This adds layers to the model, including an input layer with 2 nodes and a sigmoid activation function, and an output layer with 1 node and a sigmoid activation function.
4. Compiling the model - This compiles the model with the binary cross entropy loss function and the Adam optimizer.
5. Fitting the model - This fits the model to the data given by X and y.
6. Evaluating the model - This evaluates the model and prints out the accuracy of the model.

For more information, please refer to the following links:

• Keras Documentation
• Keras Sequential Model Guide
• Keras Layers Guide
• Keras Loss Functions Guide
• Keras Optimizers Guide

Edit this code on GitHub