UNSUPERVISED MACHINE LEARNING SEMINAR
The high growing in the volume and variety of data, and their use in big data analytics, leads to a growing interest in unsupervised machine learning technologies. Since tagging such quantities of data is infeasible, unsupervised methodologies have been developed to allow systems to analyze and utilize this data - including clustering, probability density estimation, dimensionality reduction, visualization, and more.
Focusing on the theoretical and practical aspects of unsupervised learning, the Unsupervised Machine Learning Online Seminar has accompanied Afeka’s Speech Processing Conference as a satellite event for the past five years.
This year, Prof. Brendan Murphy from University College Dublin has agreed to share his knowledge with us as the satellite seminar’s keynote speaker.