Hands-On Neural Networks with TensorFlow 2.0

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  • Grasp machine learning and neural network techniques to solve challenging tasks
  • Apply the new features of TF 2.0 to speed up development
  • Use TensorFlow Datasets (tfds) and the tf.data API to build high-efficiency data input pipelines
  • Perform transfer learning and fine-tuning with TensorFlow Hub
  • Define and train networks to solve object detection and semantic segmentation problems
  • Train Generative Adversarial Networks (GANs) to generate images and data distributions
  • Use the SavedModel file format to put a model, or a generic computational graph, into production

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.

  • Understand the basics of machine learning and discover the power of neural networks and deep learning
  • Explore the structure of the TensorFlow framework and understand how to transition to TF 2.0
  • Solve any deep learning problem by developing neural network-based solutions using TF 2.0
Page Count 358
Course Length 10 hours 44 minutes
ISBN 9781789615555
Date Of Publication 18 Sep 2019


Paolo Galeone

Paolo Galeone is a computer engineer with strong practical experience. After getting his MSc degree, he joined the Computer Vision Laboratory at the University of Bologna, Italy, as a research fellow, where he improved his computer vision and machine learning knowledge working on a broad range of research topics. Currently, he leads the Computer Vision and Machine Learning laboratory at ZURU Tech, Italy. In 2019, Google recognized his expertise by awarding him the title of Google Developer Expert (GDE) in Machine Learning. As a GDE, he shares his passion for machine learning and the TensorFlow framework by blogging, speaking at conferences, contributing to open-source projects, and answering questions on Stack Overflow.