Buch, Englisch, 94 Seiten, Format (B × H): 155 mm x 235 mm
Human-in-the-Loop for Quality Data
Buch, Englisch, 94 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: SpringerBriefs in Applied Sciences and Technology
ISBN: 978-3-032-29480-7
Verlag: Springer Nature Switzerland AG
This open access book presents a “discount”-quality approach to data preparation for scientific data analysis, a critical prerequisite in modern applications such as data analysis projects, Artificial Intelligence, and Machine Learning. It discusses advanced techniques for fostering responsible data science, i.e., designing sustainable data analysis pipelines based on Human-In-The-Loop (HITL) approaches to achieve high-quality data. It investigates developing task- and context-driven sustainable approaches for data preparation, drawing on methods and theories to reduce annotations and processing space and time, and considering the estimation of the necessary human computing effort and the requirements of the specific task. The contributions address key aspects related to data ecosystems, data preparation pipelines, data quality evaluation and improvement, on-demand approaches to data preparation, data enrichment, and human factors in data preparation.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken
Weitere Infos & Material
Discount Quality for Responsible Data Science: Human-in-the-Loop for Quality Data.- Discount Quality for Responsible Data Science: Human-in-the-Loop for Quality Data.- Discount Quality for Responsible Data Science: Human-in-the-Loop for Quality Data.- Discount Quality for Responsible Data Science: Human-in-the-Loop for Quality Data.- Discount Quality for Responsible Data Science: Human-in-the-Loop for Quality Data.
