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Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026
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Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026

Discount Quality for Responsible Data ScienceHuman-in-the-Loop for Quality Data

Author(s): Barbara Pernici, Tiziana Catarci, Matteo Palmonari, Giovanni Simonini

Format: Paperback

Publisher: Springer Nature Switzerland AG, Switzerland

Imprint: Springer Nature Switzerland AG

ISBN-13: 9783032294807, 978-3032294807

Synopsis

Thisopen accessbook presentsa 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, [url] designing sustainable data analysis pipelines based on Human-In-The-Loop (HITL) approaches to achieve high-quality data. It investigatesdeveloping 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 co.

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Discount Quality for Responsible Data Science by Barbara Pernici | PB | 2026

Discount Quality for Responsible Data ScienceHuman-in-the-Loop for Quality Data

Author(s): Barbara Pernici, Tiziana Catarci, Matteo Palmonari, Giovanni Simonini

Format: Paperback

Publisher: Springer Nature Switzerland AG, Switzerland

Imprint: Springer Nature Switzerland AG

ISBN-13: 9783032294807, 978-3032294807

Synopsis

Thisopen accessbook presentsa 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, [url] designing sustainable data analysis pipelines based on Human-In-The-Loop (HITL) approaches to achieve high-quality data. It investigatesdeveloping 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 co.

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Product Description

Discount Quality for Responsible Data ScienceHuman-in-the-Loop for Quality Data

Author(s): Barbara Pernici, Tiziana Catarci, Matteo Palmonari, Giovanni Simonini

Format: Paperback

Publisher: Springer Nature Switzerland AG, Switzerland

Imprint: Springer Nature Switzerland AG

ISBN-13: 9783032294807, 978-3032294807

Synopsis

Thisopen accessbook presentsa 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, [url] designing sustainable data analysis pipelines based on Human-In-The-Loop (HITL) approaches to achieve high-quality data. It investigatesdeveloping 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 co.

Product Specifications

General

Brand

Springer Nature Switzerland AG

format

trade paperback

Language

english

series

springerbriefs in applied sciences and technology ser.

type

textbook

age level

adults

Size

15.6 x 0.6 x 23.4 cm

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