python-kerasHow do I create a Python Keras model?

Creating a Keras model in Python is a straightforward process. First, import the necessary libraries:

import keras
from keras.models import Sequential
from keras.layers import Dense

Then, define the model architecture:

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

The first layer has 64 nodes, a ReLU activation, and takes input of dimension 100. The second layer has 10 nodes and a Softmax activation.

Next, compile the model:

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

This specifies the loss function, optimizer, and metrics for the model.

Finally, train the model:

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

This trains the model on the training data for 5 epochs with a batch size of 32.

The complete code should look something like this:

import keras
from keras.models import Sequential
from keras.layers import Dense

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

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

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

Helpful links

• Keras Documentation
• Getting Started with Keras

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