Book Image

The Deep Learning Workshop

By : Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So
Book Image

The Deep Learning Workshop

By: Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So

Overview of this book

Are you fascinated by how deep learning powers intelligent applications such as self-driving cars, virtual assistants, facial recognition devices, and chatbots to process data and solve complex problems? Whether you are familiar with machine learning or are new to this domain, The Deep Learning Workshop will make it easy for you to understand deep learning with the help of interesting examples and exercises throughout. The book starts by highlighting the relationship between deep learning, machine learning, and artificial intelligence and helps you get comfortable with the TensorFlow 2.0 programming structure using hands-on exercises. You’ll understand neural networks, the structure of a perceptron, and how to use TensorFlow to create and train models. The book will then let you explore the fundamentals of computer vision by performing image recognition exercises with convolutional neural networks (CNNs) using Keras. As you advance, you’ll be able to make your model more powerful by implementing text embedding and sequencing the data using popular deep learning solutions. Finally, you’ll get to grips with bidirectional recurrent neural networks (RNNs) and build generative adversarial networks (GANs) for image synthesis. By the end of this deep learning book, you’ll have learned the skills essential for building deep learning models with TensorFlow and Keras.
Table of Contents (9 chapters)
Preface

Digital Images

Humans can see through their eyes by transforming light into electrical signals that are then processed by the brain. But computers do not have physical eyes to capture light. They can only process information in digital forms composed of bits (0 or 1). So, to be able to “see", computers require a digitized version of an image.

A digital image is formed by a two-dimensional matrix of pixels. For a grayscale image, each of these pixels can take a value between 0 and 255 that represents its intensity or level of gray. A digital image can be composed of one channel for a black and white image or three channels (red, blue, and green) for a color image:

Figure 3.2: Digital representation of an image

A digital image is characterized by its dimensions (height, width, and channel):

  • Height: How many pixels there are on the vertical axis.
  • Width: How many pixels there are on the horizontal axis.
  • Channel: How many channels...