Machine learning applied to Agricultural Production

Programa de Pós-Graduação Stricto Sensu em Engenharia de Produção


The course work will be in English and will teach the students to solve problems in large database using machine learning systems.Machine-learning paradigms for selecting input variables. Data Mining: Practical Machine Learning Tools and applications. Applications in agricultural production.


Newly published paper will be used to guide the problem solving techniques. Please see some examples below: 
BORCHERS, M.R. ; CHANG, Y.M.; PROUDFOOT, K.L.; WADSWORTH, B.A.;  STONE, A.E.; BEWLEY, J.M.  Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle. Journal of Dairy Science, v. 100, n. 7, p. 5664-5674, 2017. ISSN 0022-0302,
McQUEEN, Robert J. et. Al. Applying Machine Learning to Agricultural Data. 1994.
MUTTIL, N.; CHAU, Kwok-Wing. Machine-learning paradigms for selecting ecologically significant input variables. Engineering Applications of Artificial Intelligence, v. 20, n. 6, p. 735-744, 2007. ISSN 0952-1976,
VALLETTA, J.J.; TORNEY, C.; KINGS, M.; THORNTON, A.; MADDEN, J. Applications of machine learning in animal behaviour studies. Animal Behaviour, v. 124, p. 203-220, 2017. ISSN 0003-3472,