Evolutionary Deep Neural Architecture Search: Fundamentals, Methods, and Recent Advances
Nov 2022 · Studies in Computational Intelligence Buku 1070 · Springer Nature
eBook
331
Halaman
reportRating dan ulasan tidak diverifikasi Pelajari Lebih Lanjut
Tentang eBook ini
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.
Beri rating eBook ini
Sampaikan pendapat Anda.
Informasi bacaan
Smartphone dan tablet
Instal aplikasi Google Play Buku untuk Android dan iPad/iPhone. Aplikasi akan disinkronkan secara otomatis dengan akun Anda dan dapat diakses secara online maupun offline di mana saja.
Laptop dan komputer
Anda dapat mendengarkan buku audio yang dibeli di Google Play menggunakan browser web komputer.
eReader dan perangkat lainnya
Untuk membaca di perangkat e-ink seperti Kobo eReaders, Anda perlu mendownload file dan mentransfernya ke perangkat Anda. Ikuti petunjuk Pusat bantuan yang mendetail untuk mentransfer file ke eReaders yang didukung.
