Centrality and Diversity in Search - Biswas, Anirban
- Format: Broché Voir le descriptif
Vous en avez un à vendre ?
Vendez-le-vôtre70,91 €
Produit Neuf
Ou 17,73 € /mois
- Livraison à 0,01 €
- Livré entre le 4 et le 11 mai
Brand new, In English, Fast shipping from London, UK; Tout neuf, en anglais, expédition rapide depuis Londres, Royaume-Uni;ria9783030247126_dbm
- Payez directement sur Rakuten (CB, PayPal, 4xCB...)
- Récupérez le produit directement chez le vendeur
- Rakuten vous rembourse en cas de problème
Gratuit et sans engagement
Félicitations !
Nous sommes heureux de vous compter parmi nos membres du Club Rakuten !
TROUVER UN MAGASIN
Retour
Avis sur Centrality And Diversity In Search de Biswas, Anirban Format Broché - Livre Informatique
0 avis sur Centrality And Diversity In Search de Biswas, Anirban Format Broché - Livre Informatique
Les avis publiés font l'objet d'un contrôle automatisé de Rakuten.
Présentation Centrality And Diversity In Search de Biswas, Anirban Format Broché
- Livre Informatique
Résumé :
The concepts of centrality and diversity are highly important in search algorithms, and play central roles in applications of artificial intelligence (AI), machine learning (ML), social networks, and pattern recognition. This work examines the significance of centrality and diversity in representation, regression, ranking, clustering, optimization, and classification. The text is designed to be accessible to a broad readership. Requiring only a basic background in undergraduate-level mathematics, the work is suitable for senior undergraduate and graduate students, as well as researchers working in machine learning, data mining, social networks, and pattern recognition.
Biographie:
Dr. M.N. Murty is a Professor in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore, India. Anirban Biswas is a Teaching Assistant at the same institution. Prof. Murty's other publications include the Springer titles Support Vector Machines and Perceptrons, Compression Schemes for Mining Large Datasets, and Pattern Recognition: An Algorithmic Approach....
Sommaire:
The concepts of centrality and diversity are highly important in search algorithms, and play central roles in applications of artificial intelligence (AI), machine learning (ML), social networks, and pattern recognition. This work examines the significance of centrality and diversity in representation, regression, ranking, clustering, optimization, and classification. The text is designed to be accessible to a broad readership. Requiring only a basic background in undergraduate-level mathematics, the work is suitable for senior undergraduate and graduate students, as well as researchers working in machine learning, data mining, social networks, and pattern recognition. ...
Détails de conformité du produit
Personne responsable dans l'UE