Data Mining

Catalog description

Algorithmic and mathematical foundations of the Knowledge Discovery in Databases (KDD) process, including data representation, preprocessing, supervised and unsupervised learning, and recommendation systems, with emphasis on computational efficiency, scalability on massive-scale data, and performance evaluation using modern analytical tools.