Understanding of basic machine learning techniques such as Decission Trees or Neural Networks

Students are enabled to study and apply basic machine learning techniques

Definition. Basic notions. Data types. Appropriate representations of real problems used as inputs for machine learning techniques. Classification, prediction and clustering tasks. K-Nearest Neighborhood, Decision Trees, Naive Bayes Classifiers, Neural Networks, Support Vector Machines, K-Means Clustering. Model validation and testing protocols. Applications in Civil Engineering and Geosciences.