This work focuses on topic detection as a part of natural language processing (NLP).
It contains a theoretical overview of widely used methods and its verification on real
data sets. The goal of this work is to develop a chain of tasks which can automatically
cluster a given set of textual documents and determine main topics. It requires to
use methods of unsupervised machine learning to meet this goal.