What are kernel initializers in keras?

What are kernel initializers in keras?

What are kernel initializers in keras?

This recipe explains what are kernel initializers in keras


Recipe Objective

What are kernel initializers in keras?

Kernel initializers are used to statistically initialise the weights in the model. This will generate the weights and distribute them, it can be used as the starting weights

Step 1- Importing Libraries

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

Step 2- Creating a model.

We will create a model with the initializer.

# define input data X = np.array([17, 35, 400, 230]) # show input data for context print(X) # reshape input data into one sample a sample with a channel X = X.reshape((1, 2, 2, 1)) # define model model = Sequential() model.add(Dense(13, input_dim=13, kernel_initializer='normal', activation='relu')) model.summary()

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