Unsupervised Learning Help

What is Unsupervised Learning Help?

An approach to machine learning that uses data which has not been labelled. Commonly it will seek to determine characteristics that make the data points more or less similar to each other and will attempt to represent the data in a summary form, such as through clusters or common features.

Common tasks in Supervised learning Help.

In Unsupervised learning there are two most common tasks are clustering and association.

• Clustering : Clustering is a technique of grouping the objects into clusters such that objects with most similarities remain into a group and have less or no similarities with the objects of another group. Cluster analysis finds the commonalities between the data objects and categorises them as per the presence and absence of those commonalities.

• Association : An association rule is an unsupervised learning method which is used for finding the relationships between variables in the large database. It determines the set of items that occur together in the dataset. Association rule makes marketing strategy more effective.

How it is helpful for ML Students and Developers, Engineers and AI researchers.

It is useful for finding useful insights from the data. Unsupervised learning is much similar to how humans learn to think by their own experience which makes it closer to the real AI. In the real world, we do not always have input data with corresponding output so to solve such cases, we need unsupervised learning.

Important tools, packages and libraries

• Scikit-learn : It is a free software machine learning library for python programming.

  • K-means clustering

  • Hierarchical clustering

  • Principal Component Analysis

  • Independent Component Analysis

  • Apriori algorithm

  • Singular value decomposition