Data pre-processing/feature selection and exploratory analysis with WEKA.
Clustering (k-means, ΕΜ)
Classification (naive Bayes & decision trees)
Web Advertising Lab
Our 2013 data mining class.
Machine Learning & Data Mining (Spring Semester)
The dbnet aims to familiarize students with advanced methods of data mining and learning from data sets that are characterized by complexity and heterogeneity.
The machine learning algorithms are interesting solutions for modern problems such as assessing medical data for diagnosis, prediction, and detection of structure in biological and medical data, formulation of recommendations on websites, techniques for online advertising campaigns, etc.
Supervised Learning: Prediction Techniques: Linear Regression, Model Selection, Generalized Linear Models, Support Vector Machines, Kernels