
Give the Gift of Choice!
Too many options? Treat your friends and family to their favourite stores with a Bayshore Shopping Centre gift card, redeemable at participating retailers throughout the centre. Click below to purchase yours today!Purchase HereHome
Machine Learning: Theoretical Foundations and Practical Applications
Coles
Loading Inventory...
Machine Learning: Theoretical Foundations and Practical Applications in Ottawa, ON
Current price: $262.95


Machine Learning: Theoretical Foundations and Practical Applications in Ottawa, ON
Current price: $262.95
Loading Inventory...
Size: Paperback
*Product information may vary - to confirm product availability, pricing, shipping and return information please contact Coles
This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9-12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.
This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9-12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.

















