This book systematically narrates the fundamentals, methods, and recent
advances of evolutionary deep neural architecture search chapter by
chapter. This will provide the target readers with sufficient details
learning from scratch. In particular, the method parts are devoted to
the architecture search of unsupervised and supervised deep neural
networks. The people, who would like to use deep neural networks but
have no/limited expertise in manually designing the optimal deep
architectures, will be the main audience. This may include the
researchers who focus on developing novel evolutionary deep architecture
search methods for general tasks, the students who would like to study
the knowledge related to evolutionary deep neural architecture search
and perform related research in the future, and the practitioners from
the fields of computer vision, natural language processing, and others
where the deep neural networks have been successfully and largely used
in their respective fields.