Discount quality responsible data (19 résultats)

Paperback or Softback. Etat : New. Discount Quality for Responsible Data Science: Human-In-The-Loop for Quality Data. Book.

Paperback. Etat : New. 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.…

Etat : New.

Paperback. Etat : New. 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.…

Paperback. Etat : Brand New. 109 pages. 6.14x0.24x9.21 inches. In Stock.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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, i.e., 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 computing effort and the requirements of the specific task. The contributionsaddress.…

Paperback. Etat : New. 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.…

Etat : NEW.

Etat : New.

Softcover/Taschenbuch. Etat : Neu. 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. Sprache: Englisch Gewicht in Gramm: 189.…

Taschenbuch. Etat : Neu. Discount Quality for Responsible Data Science | Human-in-the-Loop for Quality Data | Barbara Pernici (u. a.) | Taschenbuch | SpringerBriefs in Applied Sciences and Technology | ix | Englisch | 2026 | Springer | EAN 9783032294807 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Paperback. Etat : New. 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.…

Etat : new. Questo è un articolo print on demand.

Paperback. Etat : new. Paperback. 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. mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Etat : Brand New. 109 pages. 6.14x0.24x9.21 inches. In Stock. This item is printed on demand.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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, i.e., 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 computing effort and the requirements of the specific task. The contributionsaddress 100 pp. Englisch.…

Paperback. Etat : new. Paperback. 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. mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Etat : new. Paperback. 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. mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; mso-border-alt: none windowtext 0cm; This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Nature Customer Service Center GmbH, Europaplatz 3,69115 Heidelberg, Germany, 69115 Heidelberg 116 pp. Englisch.…