What are kernel initializers in keras?

This recipe explains what are kernel initializers in keras

Recipe Objective

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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