Deep Learning and AI Superhero

Practical Exercises Chapter 3

Exercise 1: Saving and Loading a Keras Model

Task: Train a simple neural network on the MNIST dataset, save the model using the SavedModel format, and then load the saved model to make predictions on the test set.

Solution:

import tensorflow as tf

from tensorflow.keras.models import Sequential

from tensorflow.keras.layers import Dense, Flatten

from tensorflow.keras.datasets import mnist

# Load the MNIST dataset

(X_train, y_train), (X_test, y_test) = mnist.load_data()

# Normalize the data

X_train, X_test = X_train / 255.0, X_test / 255.0

# Define a simple Sequential model

model = Sequential([

Flatten(input_shape=(28, 28)),

Dense(128, activation='relu'),

Dense(64, activation='relu'),

Dense(10, activation='softmax')

]) ...