What is pattern recognition?
Pattern recognition is a problem of both supervised and unsupervised machine learning concerned with finding patterns and valuable insights in data. Classification and clustering are examples of pattern recognition. They are both aimed to increase the understanding of data and draw useful information from it.
Why is it important?
Pattern recognition comes in handy when there is plenty of data and you want to find any hidden insights in it. Like clustering or classification, pattern recognition allows you to understand your data better and what you can do with it.