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


The following exercises are of fundamental importance and you are invited to answer to every theoretical question and solve all of the code challenges presented:

  1. What is the semantic segmentation?
  2. Why is semantic segmentation a difficult problem?
  3. What is deconvolution? Is the deconvolution operation in deep learning a real deconvolution operation?
  4. It is possible to use Keras models as layers?
  5. Is it possible to use a single Keras Sequential model to implement a model architecture with skip connections?
  6. Describe the original U-Net architecture: what are the differences between the custom implementation presented in this chapter and the original one?
  7. Implement, using Keras, the original U-Net architecture.
  8. What is a DatasetBuilder?
  9. Describe the hierarchical organization of TensorFlow Datasets.
  10. The _info method contains the description of every single example of the dataset...