TY - GEN N2 - 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. DO - 10.1007/978-981-33-6518-6 DO - doi AB - 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. T1 - Machine learning :theoretical foundations and practical applications / AU - Pandey, Manjusha, AU - Rautaray, Siddharth Swarup, VL - volume 87 CN - Q325.5 ID - 1436083 KW - Machine learning KW - Apprentissage automatique SN - 9789813365186 SN - 9813365188 TI - Machine learning :theoretical foundations and practical applications / LK - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-33-6518-6 UR - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-33-6518-6 ER -