Book Image

Hands-On Neural Networks with TensorFlow 2.0

By : Paolo Galeone
Book Image

Hands-On Neural Networks with TensorFlow 2.0

By: Paolo 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)
Free Chapter
Section 1: Neural Network Fundamentals
Section 2: TensorFlow Fundamentals
Section 3: The Application of Neural Networks

Neural Networks and Deep Learning

Neural networks are the main machine learning models that we will be looking at in this book. Their applications are countless, as are their application fields. These range from computer vision applications (where an object should be localized in an image), to finance (where neural networks are applied to detect frauds), passing trough trading, to reaching even the art field, where neural networks are used together with the adversarial training process to create models that are able to generate new and unseen kinds of art with astonishing results.

This chapter, which is perhaps the richest in terms of theory in this whole book, shows you how to define neural networks and how to make them learn. To begin, the mathematical formula for artificial neurons will be presented, and we will highlight why a neuron must have certain features to be able to...