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| Titre : |
Apply data science : introduction, applications and projects |
| Type de document : |
texte imprimé |
| Auteurs : |
Thomas Barton, Editeur scientifique ; Christian Müller (19..-....), Editeur scientifique |
| Editeur : |
Wiesbaden : Springer Vieweg |
| Année de publication : |
2023 |
| Importance : |
232 p. |
| Format : |
24 cm |
| ISBN/ISSN/EAN : |
978-3-658-38797-6 |
| Note générale : |
Notes bibliogr. |
| Langues : |
Anglais (eng) |
| Catégories : |
Livres
|
| Tags : |
Apprentissage automatique Applications industrielles Exploration de données Aspect moral |
| Index. décimale : |
006.31 Apprentissage automatique |
| Résumé : |
This book offers an introduction to the topic of data science based on the visual processing of data. It deals with ethical considerations in the digital transformation and presents a process framework for the evaluation of technologies. It also explains special features and findings on the failure of data science projects and presents recommendation systems in consideration of current developments. Machine learning functionality in business analytics tools is compared and the use of a process model for data science is shown.The integration of renewable energies using the example of photovoltaic systems, more efficient use of thermal energy, scientific literature evaluation, customer satisfaction in the automotive industry and a framework for the analysis of vehicle data serve as application examples for the concrete use of data science. The book offers important information that is just as relevant for practitioners as for students and teachers. |
Apply data science : introduction, applications and projects [texte imprimé] / Thomas Barton, Editeur scientifique ; Christian Müller (19..-....), Editeur scientifique . - Wiesbaden : Springer Vieweg, 2023 . - 232 p. ; 24 cm. ISBN : 978-3-658-38797-6 Notes bibliogr. Langues : Anglais ( eng)
| Catégories : |
Livres
|
| Tags : |
Apprentissage automatique Applications industrielles Exploration de données Aspect moral |
| Index. décimale : |
006.31 Apprentissage automatique |
| Résumé : |
This book offers an introduction to the topic of data science based on the visual processing of data. It deals with ethical considerations in the digital transformation and presents a process framework for the evaluation of technologies. It also explains special features and findings on the failure of data science projects and presents recommendation systems in consideration of current developments. Machine learning functionality in business analytics tools is compared and the use of a process model for data science is shown.The integration of renewable energies using the example of photovoltaic systems, more efficient use of thermal energy, scientific literature evaluation, customer satisfaction in the automotive industry and a framework for the analysis of vehicle data serve as application examples for the concrete use of data science. The book offers important information that is just as relevant for practitioners as for students and teachers. |
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