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Hands-On Neural Networks with TensorFlow 2.0

Hands-On Neural Networks with TensorFlow 2.0

By : Galeone
3.7 (7)
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Hands-On Neural Networks with TensorFlow 2.0

Hands-On Neural Networks with TensorFlow 2.0

3.7 (7)
By: Galeone

Overview of this book

TensorFlow, the most popular and widely used machine learning framework, has made it possible for almost anyone to develop machine learning solutions with ease. With TensorFlow (TF) 2.0, you'll explore a revamped framework structure, offering a wide variety of new features aimed at improving productivity and ease of use for developers. This book covers machine learning with a focus on developing neural network-based solutions. You'll start by getting familiar with the concepts and techniques required to build solutions to deep learning problems. As you advance, you’ll learn how to create classifiers, build object detection and semantic segmentation networks, train generative models, and speed up the development process using TF 2.0 tools such as TensorFlow Datasets and TensorFlow Hub. By the end of this TensorFlow book, you'll be ready to solve any machine learning problem by developing solutions using TF 2.0 and putting them into production.
Table of Contents (15 chapters)
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1
Section 1: Neural Network Fundamentals
4
Section 2: TensorFlow Fundamentals
8
Section 3: The Application of Neural Networks

Getting the data

The task we are going to solve in this chapter is a classification problem on a dataset of flowers, which is available in tensorflow-datasets (tfds). The dataset's name is tf_flowers and it consists of images of five different flower species at different resolutions. Using tfds, gathering the data is straightforward, and we can get the dataset's information by looking at the info variable returned by the tfds.load invocation, as shown here:

(tf2)

import tensorflow_datasets as tfds

dataset, info = tfds.load("tf_flowers", with_info=True)
print(info)

The preceding code produces the following dataset description:

tfds.core.DatasetInfo(
name='tf_flowers',
version=1.0.0,
description='A large set of images of flowers',
urls=['http://download.tensorflow.org/example_images/flower_photos.tgz'],
features=FeaturesDict...

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