Deep Learning and AI Superhero

Practical Exercises Chapter 2

Exercise 1: Saving and Loading a TensorFlow Model

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

Solution:

import tensorflow as tf

from tensorflow.keras.datasets import mnist

from tensorflow.keras.models import Sequential

from tensorflow.keras.layers import Dense, Flatten

# 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

# Build a simple neural network model

model = Sequential([

Flatten(input_shape=(28, 28)),

Dense(128, activation='relu'),

Dense(64, activation='relu'),

Dense(