Unsupervised Deep Learning: Taxonomy and algorithms

Clustering is a fundamental challenge in many data-driven application fields and machine learning techniques. The data distribution determines the quality of outcomes, which has significant impact on clustering performance. As result, deep neural networks can be used to learn more accurate representations for clustering. Many recent studies have focused employing develop clustering-friendly representation, resulted improvement We present systematic survey with this study. Then, taxonomy proposed, as well some sample algorithms our overview. Finally, we discuss exciting future possibilities using offer remarks.