IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning

Joao Gama

ISBN 10: 3030667693 / ISBN 13: 9783030667696

Verlag: Springer International Publishing Jan 2021, 2021

Beschreibung

This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes selected papers from the Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams 2020, andFirst International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning, ITEM 2020, co-located with ECML/PKDD 2020 and held in September 2020. Due to the COVID-19 pandemic the workshops were held online.The 21 full papers and 3 short papers presented in this volume were thoroughly reviewed and selected from 35 submissions and are organized according to the workshops and their topics:IoT Streams 2020:Stream Learning;Feature Learning; ITEM 2020:Unsupervised Machine Learning; Hardware; Methods;Quantization. 328 pp. Englisch.

Bestandsnummer des Verkäufers 9783030667696

Bibliografische Details

• Titel: IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning
• Verlag: Springer International Publishing Jan 2021
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 3030667693
• ISBN-13: 9783030667696
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

This book constitutes selected papers from the Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams 2020, and First International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning, ITEM 2020, co-located with ECML/PKDD 2020 and held in September 2020. Due to the COVID-19 pandemic the workshops were held online. 

The 21 full papers and 3 short papers presented in this volume were thoroughly reviewed and selected from 35 submissions and are organized according to the workshops and their topics: IoT Streams 2020: Stream Learning; Feature Learning; ITEM 2020: Unsupervised Machine Learning; Hardware; Methods; Quantization.