Predictive Data Mining
This curricular unit has as primary goal to allow students to gain a fundamental understanding of Predictive Analytics. This course will cover the basics of predictive analytics and modeling data to determine which algorithms to use. Understand the similarities and differences and which options affect the models most. Topics covered include predictive analytics algorithms for supervised learning, including decision trees, neural networks, k-nearest neighbor, support vector machines, and model ensembles. At the end of the course, participants will be able to use these skills to produce a fully processed data set compatible with building robust predictive models that can be deployed to increase profitability.
Roberto André Pereira Henriques
Weekly - Available soon
Total - Available soon
Portuguese. If there are Erasmus students, classes will be taught in English
Programs where the course is taught: