Research Topics in ML & DL

This course explores research being done in machine learning and deep learning. Topics covered include neural networks and deep neural networks. First learners examine how to prevent neural networks from overfitting. You will explore research on multilabel learning algorithms multilabel classification and multiple-output classifications which are variants of the standard classification problem. Then examine deep learning algorithms the enhanced performance of deeper neural networks that are more adept at automatic feature extraction. Next ut facial alignment regression tree ensembles and deep features for scene recognition. Review ELM (Extreme Learning Machine) and how it is used to perform regression and multiclass classification.