python-kerasHow do I create a Python Keras neural network tutorial?

Creating a Python Keras neural network tutorial is a great way to get started with deep learning. The following example code creates a basic neural network using Keras' Sequential model API:

# Import necessary modules
from keras.models import Sequential
from keras.layers import Dense

# Create a Sequential model
model = Sequential()

# Add layers to the model
model.add(Dense(units=64, activation='relu', input_dim=100))
model.add(Dense(units=10, activation='softmax'))

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

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

Code explanation

1. Import necessary modules - This imports the necessary modules from Keras for creating a neural network.
2. Create a Sequential model - This creates a sequential model object from the Keras Sequential class.
3. Add layers to the model - This adds layers to the model with the Dense class. The number of units and activation functions can be specified here.
4. Compile the model - This compiles the model with a loss function, optimizer, and metrics.
5. Train the model - This trains the model with the x_train and y_train data. The number of epochs and batch size can be specified here.

Helpful links

• Keras Documentation
• Keras Sequential Model Guide
• Keras Dense Layer Guide

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