ISBN: 9781088200032 - intelligent machine learning-based personalized nutrition recommendation for women (9 risultati)

- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 25,72
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.

- Brossura
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 29,98
EUR 11,84 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: Brand New. 114 pages. 6.00x0.24x9.00 inches. In Stock.

- Brossura
- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 25,71
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibile
Paperback. Condizione: new. Paperback. Personalized nutrition is increasingly influenced by advances in data science, artificial intelligence, and machine learning. Intelligent Machine Learning-Based Personalized Nutrition Recommendation for Women provides a focused technical examination of how computational methods can be applied to nutrition recommendation and individualized dietary decision support. The book brings together machine learning, nutrition science, data analysis, recommendation systems, health informatics, and personalized dietary modeling within a structured interdisciplinary framework.The book introduces the foundations of personalized nutrition and explains the importance of considering individual characteristics when developing dietary recommendations. Factors such as nutritional requirements, dietary patterns, food preferences, lifestyle characteristics, demographic information, and other relevant personal variables can influence the suitability of a nutrition recommendation. The text examines these considerations from a computational and nutrition-science perspective.A central focus is placed on machine learning-based recommendation methods. The book discusses how structured nutrition and user-related data can be represented, processed, and analyzed to identify patterns and generate personalized recommendations. Concepts including data preprocessing, feature selection, classification, prediction, clustering, recommendation models, model training, and evaluation are considered in relation to intelligent nutrition systems.The book further explores the relationship between machine learning and personalized dietary recommendations for women. Women's nutritional needs can vary across different stages of life and according to individual circumstances, making personalization an important consideration in computational nutrition systems. The discussion examines how user characteristics and dietary information can be incorporated into recommendation frameworks while emphasizing the importance of appropriate data representation and model evaluation. Intelligent Machine Learning-Based Personalized Nutrition Recommendation for Women explores the application of machine learning and intelligent recommendation methods to personalized nutrition. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

- Brossura
- Print on Demand
Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 27,34
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

- Brossura
- Print on Demand
Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 25,83
EUR 3,89 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

- Brossura
- Print on Demand
Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 34,19
EUR 33,00 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibile
Paperback. Condizione: new. Paperback. Personalized nutrition is increasingly influenced by advances in data science, artificial intelligence, and machine learning. Intelligent Machine Learning-Based Personalized Nutrition Recommendation for Women provides a focused technical examination of how computational methods can be applied to nutrition recommendation and individualized dietary decision support. The book brings together machine learning, nutrition science, data analysis, recommendation systems, health informatics, and personalized dietary modeling within a structured interdisciplinary framework.The book introduces the foundations of personalized nutrition and explains the importance of considering individual characteristics when developing dietary recommendations. Factors such as nutritional requirements, dietary patterns, food preferences, lifestyle characteristics, demographic information, and other relevant personal variables can influence the suitability of a nutrition recommendation. The text examines these considerations from a computational and nutrition-science perspective.A central focus is placed on machine learning-based recommendation methods. The book discusses how structured nutrition and user-related data can be represented, processed, and analyzed to identify patterns and generate personalized recommendations. Concepts including data preprocessing, feature selection, classification, prediction, clustering, recommendation models, model training, and evaluation are considered in relation to intelligent nutrition systems.The book further explores the relationship between machine learning and personalized dietary recommendations for women. Women's nutritional needs can vary across different stages of life and according to individual circumstances, making personalization an important consideration in computational nutrition systems. The discussion examines how user characteristics and dietary information can be incorporated into recommendation frameworks while emphasizing the importance of appropriate data representation and model evaluation. Intelligent Machine Learning-Based Personalized Nutrition Recommendation for Women explores the application of machine learning and intelligent recommendation methods to personalized nutrition. 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.…

- Brossura
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 29,85
EUR 43,79 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibile
Paperback. Condizione: new. Paperback. Personalized nutrition is increasingly influenced by advances in data science, artificial intelligence, and machine learning. Intelligent Machine Learning-Based Personalized Nutrition Recommendation for Women provides a focused technical examination of how computational methods can be applied to nutrition recommendation and individualized dietary decision support. The book brings together machine learning, nutrition science, data analysis, recommendation systems, health informatics, and personalized dietary modeling within a structured interdisciplinary framework.The book introduces the foundations of personalized nutrition and explains the importance of considering individual characteristics when developing dietary recommendations. Factors such as nutritional requirements, dietary patterns, food preferences, lifestyle characteristics, demographic information, and other relevant personal variables can influence the suitability of a nutrition recommendation. The text examines these considerations from a computational and nutrition-science perspective.A central focus is placed on machine learning-based recommendation methods. The book discusses how structured nutrition and user-related data can be represented, processed, and analyzed to identify patterns and generate personalized recommendations. Concepts including data preprocessing, feature selection, classification, prediction, clustering, recommendation models, model training, and evaluation are considered in relation to intelligent nutrition systems.The book further explores the relationship between machine learning and personalized dietary recommendations for women. Women's nutritional needs can vary across different stages of life and according to individual circumstances, making personalization an important consideration in computational nutrition systems. The discussion examines how user characteristics and dietary information can be incorporated into recommendation frameworks while emphasizing the importance of appropriate data representation and model evaluation. Intelligent Machine Learning-Based Personalized Nutrition Recommendation for Women explores the application of machine learning and intelligent recommendation methods to personalized nutrition. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

- Brossura
- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 41,40
EUR 35,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Personalized nutrition is increasingly influenced by advances in data science, artificial intelligence, and machine learning. Intelligent Machine Learning-Based Personalized Nutrition Recommendation for Women provides a focused technical examination of how computational methods can be applied to nutrition recommendation and individualized dietary decision support. The book brings together machine learning, nutrition science, data analysis, recommendation systems, health informatics, and personalized dietary modeling within a structured interdisciplinary framework.The book introduces the foundations of personalized nutrition and explains the importance of considering individual characteristics when developing dietary recommendations. Factors such as nutritional requirements, dietary patterns, food preferences, lifestyle characteristics, demographic information, and other relevant personal variables can influence the suitability of a nutrition recommendation. The text examines these considerations from a computational and nutrition-science perspective.A central focus is placed on machine learning-based recommendation methods. The book discusses how structured nutrition and user-related data can be represented, processed, and analyzed to identify patterns and generate personalized recommendations. Concepts including data preprocessing, feature selection, classification, prediction, clustering, recommendation models, model training, and evaluation are considered in relation to intelligent nutrition systems.The book further explores the relationship between machine learning and personalized dietary recommendations for women. Women's nutritional needs can vary across different stages of life and according to individual circumstances, making personalization an important consideration in computational nutrition systems. The discussion examines how user characteristics and dietary information can be incorporated into recommendation frameworks while emphasizing the importance of appropriate data representation and model evaluation.…

- Brossura
- Print on Demand
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 32,30
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Intelligent Machine Learning-Based Personalized Nutrition Recommendation for Women | Trisha | Taschenbuch | Englisch | 2026 | Nala Kala | EAN 9781088200032 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…