Preface
The release of TensorFlow 2.x in 2019 was one of the biggest and most anticipated events in the deep learning and artificial intelligence arena, because it brought with it long-overdue improvements to this popular and relevant framework, mainly focused on simplicity and ease of use.
The adoption of Keras as the official TensorFlow high-level API, the ability to switch back and forth between eager and graph-based execution (thanks to tf.function), and the ability to create complex data pipelines with tf.data are just a few of the great additions that TensorFlow 2.x brings to the table.
In this book, you will discover a vast amount of recipes that will teach you how to take advantage of these advancements in the context of deep learning applied to computer vision. We will cover a wide gamut of applications, ranging from image classification to more challenging ones, such as object detection, image segmentation, and Automated Machine Learning (AutoML).
By the end of this book, you’ll be prepared and confident enough to tackle any computer vision problem that comes your way with the invaluable help of TensorFlow 2.x!
