Data mining aims at discovering knowledge from the data. Supervised and unsupervised machine learning are two major branches inside data analytics. There are some methodologies to deal with the data mining flow, beginning with raw data and ending with a prediction model to work accurately with unseen data. This seminar explains different approaches as well as specific frameworks with special attention in the lectures for undergraduate, master and postgraduate students. Depending on the level and the initial background some of the may be more focused to the pursued goal.
31/05/2019 13:00
Inteligent Systems
Antonio J. Tallón-Ballesteros received the Technical Engineer degree in Systems Computer Science from the University of Córdoba, Spain, in 2002, the M.Sc. degree in Computer Science from the University of Granada, Spain, in 2004, and the Ph.D. degree in Computer Science from the University of Seville, Spain, in 2013. He also got the accreditation for Senior Lecturer in 2013. He was a Lecturer from 2005 till 2018 at University of Seville, Spain. Since 2018, He has been a PhD Lecturer at the University of Huelva, Spain. He has more than 40 publications. Among them, it is worth mentioning more than 10 international journals in different publishing houses (Springer, Elsevier, Taylor & Francis and IOS Press), 15 contributions in international conferences. He has also edited international conference proceedings 7 times in Springer and IOS Press publishers. His current research areas include data mining, soft computing and data pre-processing.
