Advanced Deep Learning with TensorFlow 2 and Keras – Second Edition

In recent years, Deep Learning has made unprecedented success stories in difficult
problems in vision, speech, natural language processing and understanding, and
all other areas with abundance of data. The interest in this field from companies,
universities, governments, and research organizations has accelerated the advances
in the field. This book covers select important topics in Deep Learning with three
new chapters, Object Detection, Semantic Segmentation, and Unsupervised Learning using
Mutual Information. The advanced theories are explained by giving a background
of the principles, digging into the intuition behind the concepts, implementing
the equations and algorithms using Keras, and examining the results.
Artificial Intelligence (AI), as it stands today, is still far from being a wellunderstood field. Deep Learning (DL), as a sub field of AI, is in the same position.
While it is far from being a mature field, many real-world applications such
as vision-based detection and recognition, autonomous navigation, product
recommendation, speech recognition and synthesis, energy conservation, drug
discovery, finance, and marketing are already using DL algorithms. Many more
applications will be discovered and built. The aim of this book is to explain advanced
concepts, give sample implementations, and let the readers as experts in their field
identify the target applications.