python-kerasHow can I use batch normalization in TensorFlow with Python and Keras?

Batch normalization is a technique used to reduce internal covariate shift and improve the training of deep neural networks. In TensorFlow with Python and Keras, it can be implemented as follows:

from tensorflow.keras.layers import BatchNormalization

model = Sequential()
model.add(BatchNormalization())

This code adds a batch normalization layer to a sequential model. The layer will normalize the input data by subtracting the batch mean and dividing by the batch standard deviation.

Code explanation

• from tensorflow.keras.layers import BatchNormalization: imports the BatchNormalization class from the tensorflow.keras.layers module
• model = Sequential(): creates a Sequential model
• model.add(BatchNormalization()): adds a BatchNormalization layer to the model

Helpful links

• TensorFlow Keras Documentation
• Batch Normalization Explained

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