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