Data Analytics and Machine Learning
Α. Πικράκης, Ι. Θεοδωρίδης. Εργ. βοηθός: Α. Τριτσαρώλης
Introduction to data analytics (principles, pipeline, pre-processing). Common Machine Learning methods (classification, clustering). Neural networks and Deep Learning. Advanced clustering techniques (DBSCAN, OPTICS, etc.). Applications on Text / audio / video data mining. Lab hours with Python, R, Matlab
ΛιγότεραIntroduction to data analytics (principles, pipeline, pre-processing). Common Machine Learning methods (classification, clustering). Neural networks and Deep Learning. Advanced clustering techniques (DBSCAN, OPTICS, etc.). Applications on Text / audio / video data mining. Lab hours with Python, R, Matlab
Introduction to data analytics (principles, pipeline, pre-processing). Common Machine Learning methods (classification, clustering). Neural networks and Deep Learning. Advanced clustering techniques (DBSCAN, OPTICS, etc.). Applications on Text / audio / video data mining. Lab hours with Python, R, Matlab
