Unsupervised Learning

In previous blog post on supervised learning, we have seen that each observed data has a label attached to it, making it easy to train a model. However, in unsupervised learning, the algorithm finds the hidden patterns in unlabeled data. A popular technique in unsupervised learning is Clustering Algorithms. Clustering Algorithms are a set of algorithms, which clusters data points based on similarity metric either measured in terms of distance or using probability to categorize the data point etc. In simple terms, we can think of clustering as a way to group the data points that are similar in nature from group of data points which are dissimilar.