How to design an ANN with the help of keras?
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How to design an ANN with the help of keras?

How to design an ANN with the help of keras?

This recipe helps you design an ANN with the help of keras

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Recipe Objective

How to design an ANN with the help of keras?

ANN stands for *Artificial neural networks*. In this we create models that are inspired by the human brains and process the information similarly to it.

Step 1- Importing Libraries

import numpy as np from tensorflow import keras from tensorflow.keras import layers from keras.models import Sequential from keras.layers import Dense

Step 2- Load the dataset.

# the data, split between train and test sets (x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()

Step 3- preprocess the dataset.

num_classes = 10 input_shape = (28, 28, 1) X_train = x_train.astype("float32") / 255 X_test = x_test.astype("float32") / 255 X_train = np.expand_dims(X_train, -1) X_test = np.expand_dims(X_test, -1) y_train = keras.utils.to_categorical(y_train, num_classes) y_test = keras.utils.to_categorical(y_test, num_classes)

Step 4- Create the model

model = keras.Sequential( [ keras.Input(shape=input_shape), layers.Conv2D(32, kernel_size=(2, 2), activation="relu"), layers.Conv2D(64, kernel_size=(2, 2), activation="sigmoid"), layers.Flatten(), layers.Dropout(0.1), layers.Dense(num_classes, activation="softmax"), ] ) model.summary()

Step 5- Fit the DataSet.

batch_size = 128 epochs = 5 model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["accuracy"]) model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, validation_split=0.1)

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