Using Convolutional Neural Networks with TensorFlow

Source: Cognitiveclass.ai

Introduction

What are Convolutions and Poolings

How filters work?
A filter which pops out vertical lines
A filter which pops out horizontal lines
a 4 x 4 pooling

Coding for convolutions and max pooling

model = tf.keras.models.Sequential([  tf.keras.layers.Flatten(input_shape=(28, 28)),
tf.keras.layers.Dense(128, activation = tf.nn.relu,
tf.keras.layers.Dense(10, activation = tf.nn.softmax
])
model = tf.keras.models.Sequential([  tf.keras.layers.Conv2D(64, (3,3), activation='relu',     input_shape=(28, 28, 1)),  tf.keras.layers.MaxPooling2D(2, 2),  tf.keras.layers.Conv2D(64, (3,3), activation='relu'),  tf.keras.layers.MaxPooling2D(2,2),  tf.keras.layers.Flatten(),  tf.keras.layers.Dense(128, activation='relu'),  tf.keras.layers.Dense(10, activation='softmax')])
tf.keras.layers.Conv2D(64, (3,3), activation='relu',     input_shape=(28, 28, 1))
tf.keras.layers.MaxPooling2D(2, 2)
Output of model.summary

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