Applied Deep Learning

Carl Chalmers, Paul Fergus

ISBN 10: 3031044193 / ISBN 13: 9783031044199

Editore: Springer International Publishing AG, CH, 2022

Riguardo questo articolo

This book focuses on the applied aspects of artificial intelligence using enterprise frameworks and technologies. The book is applied in nature and will equip the reader with the necessary skills and understanding for delivering enterprise ML technologies. It will be valuable for undergraduate and postgraduate students in subjects such as artificial intelligence and data science, and also for industrial practitioners engaged with data analytics and machine learning tasks. The book covers all of the key conceptual aspects of the field and provides a foundation for all interested parties to develop their own artificial intelligence applications.

Codice articolo LU-9783031044199

Dati bibliografici

• Titolo: Applied Deep Learning
• Editore: Springer International Publishing AG, CH
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 3031044193
• ISBN 13: 9783031044199
• Rilegatura: Hardback
• Edizione: 2022 ed.
• Condizione: New

Descrizione articolo

Riassunto

This book focuses on the applied aspects of artificial intelligence using enterprise frameworks and technologies. The book is applied in nature and will equip the reader with the necessary skills and understanding for delivering enterprise ML technologies. It will be valuable for undergraduate and postgraduate students in subjects such as artificial intelligence and data science, and also for industrial practitioners engaged with data analytics and machine learning tasks. The book covers all of the key conceptual aspects of the field and provides a foundation for all interested parties to develop their own artificial intelligence applications.

Informazioni sull?autore

Prof. Paul Fergus is a Professor in Machine Learning and Dr. Carl Chambers is a Senior Lecturer in the Dept. of Computer Science of Liverpool John Moores University. Their teaching responsibilities include Machine Learning and Data Science. Their research interest includes Applied Machine Learning, Computer Vision, Signal Processing, and Pattern Recognition.