This book presents innovative techniques in data analysis and related branches for solving problems in different areas of science. The authors present multiple techniques in data science and its applications, such as multi-objective optimization, statistical analysis, statistical process, and design of experiments for industry, artificial intelligence and machine learning, big data analytics, and stochastic processes. The methodologies used in the case studies allow practitioners to replicate and adapt the proposed models and techniques to new areas of analysis. At the same time, the book allows students from different areas to see how the implementation of data analysis can help understand phenomena in the real world and how, through a structured methodology, it is possible to derive conclusions to different problems that arise in many areas of science.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Luis Carlos Méndez-González is a research professor in the Department of Industrial Engineering and Manufacturing at the Institute of Engineering and Technology, Autonomous University of Ciudad Juárez (UACJ). He is recognized as a member of Mexico's National System of Researchers (SNII) by the SECIHTI, and has extensive experience in the automotive, medical, and manufacturing industries. His research interests and journal publications cover a wide range of topics, including reliability analysis, statistical modeling, automation, machine learning, and data science.
Isidro Jesús González-Hernández received his Ph.D. in Strategic Planning and Technology Management from the Popular Autonomous University of the State of Puebla (UPAEP). He is a professor and researcher with Bachelor's and Postgraduate degrees in Industrial Engineering from the Autonomous University of the State of Hidalgo (UAEH). He is a National Researcher within the National System of Researchers (SNII) of SECIHTI in Mexico. His research interests include the design, modeling, optimization, and simulation of supply chains and logistics systems. He also focuses on statistical modeling for reliability analysis.
Manuel Iván Rodríguez Borbón is a researcher and consultant with expertise in industrial engineering, statistics, and data analysis. He holds a Ph.D. in Industrial Engineering from New Mexico State University (NMSU), where his doctoral thesis focused on a multi-factor reliability model with a Bayesian application to accelerated life testing. He also holds a Master of Science in Statistics from the University of Texas at El Paso and a Bachelor of Science degree in Industrial Engineering from the Instituto Tecnológico de Ciudad Juarez, Mexico.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. N° de réf. du vendeur 2708886170
Quantité disponible : Plus de 20 disponibles
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents innovative techniques in data analysis and related branches for solving problems in different areas of science. The authors present multiple techniques in data science and its applications, such as multi-objective optimization, statistical analysis, statistical process, and design of experiments for industry, artificial intelligence and machine learning, big data analytics, and stochastic processes. The methodologies used in the case studies allow practitioners to replicate and adapt the proposed models and techniques to new areas of analysis. At the same time, the book allows students from different areas to see how the implementation of data analysis can help understand phenomena in the real world and how, through a structured methodology, it is possible to derive conclusions to different problems that arise in many areas of science. 503 pp. Englisch. N° de réf. du vendeur 9783032137029
Quantité disponible : 2 disponible(s)
Vendeur : preigu, Osnabrück, Allemagne
Buch. Etat : Neu. Data Analysis Techniques and Applications | Luis Carlos Méndez-González (u. a.) | Buch | EAI/Springer Innovations in Communication and Computing | xvi | Englisch | 2026 | Springer | EAN 9783032137029 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 135526237
Quantité disponible : 5 disponible(s)
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents innovative techniques in data analysis and related branches for solving problems in different areas of science. The authors present multiple techniques in data science and its applications, such as multi-objective optimization, statistical analysis, statistical process, and design of experiments for industry, artificial intelligence and machine learning, big data analytics, and stochastic processes. The methodologies used in the case studies allow practitioners to replicate and adapt the proposed models and techniques to new areas of analysis. At the same time, the book allows students from different areas to see how the implementation of data analysis can help understand phenomena in the real world and how, through a structured methodology, it is possible to derive conclusions to different problems that arise in many areas of science.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 520 pp. Englisch. N° de réf. du vendeur 9783032137029
Quantité disponible : 1 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents innovative techniques in data analysis and related branches for solving problems in different areas of science. The authors present multiple techniques in data science and its applications, such as multi-objective optimization, statistical analysis, statistical process, and design of experiments for industry, artificial intelligence and machine learning, big data analytics, and stochastic processes. The methodologies used in the case studies allow practitioners to replicate and adapt the proposed models and techniques to new areas of analysis. At the same time, the book allows students from different areas to see how the implementation of data analysis can help understand phenomena in the real world and how, through a structured methodology, it is possible to derive conclusions to different problems that arise in many areas of science. N° de réf. du vendeur 9783032137029
Quantité disponible : 1 disponible(s)