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Machine Learning Paradigms

Machine Learning Paradigms

Autorzy
Wydawnictwo Springer Nature
Data wydania 23/07/2020
Wydanie Pierwsze
Forma publikacji eBook: Reflowable eTextbook (ePub)
Język angielski
ISBN 9783030497248
Kategorie Inżynieria: pojęcia ogólne, Sztuczna inteligencja
Produkt dostępny on-line
Typ przesyłki: wysyłka kodu na adres e-mail
E-Mail
zamówienie z obowiązkiem zapłaty
Do schowka

Opis książki

At the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and diverse other disciplines. The book at hand aims at exposing its reader to some of the most significant recent advances in deep learning-based technological applications and consists of an editorial note and an additional fifteen (15) chapters. All chapters in the book were invited from authors who work in the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into six parts, namely (1) Deep Learning in Sensing, (2) Deep Learning in Social Media and IOT, (3) Deep Learning in the Medical Field, (4) Deep Learning in Systems Control, (5) Deep Learning in Feature Vector Processing, and (6) Evaluation of Algorithm Performance.  This research book is directed towards professors, researchers, scientists, engineers and students in computer science-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent deep learning-based technological applications. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into their application areas of interest.

Machine Learning Paradigms

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