SOM (Self Organizing Maps) is an Artificial Neural Network technique. It is also a data clustering and dimension reduction technique. Visualization and analyzing tool for high-dimensional data.
Moreover it's an unsupervised learning technique, which means it learns without a teacher.
Competitive learning technique. This means the neurons in the SOM learns by competing with each other to become the winner.
SOM (Self Organizing Maps) has many variations and here we are referring to Kohonen’s SOMs as SOMs.
Difference between supervised unsupervised learning
Should be there someone to provide guidance in learning? Supervised learning example can be a mother teaching you to recognize an apple, first show an apple and say the word apple. Next time you see an apple you’ll say that’s an apple. Mother is your teacher.
Unsupervised learning if you were given black/blue/red color buttons and ask you to separate depending on colors, you’ll do it by yourself probably. You won't need a teacher.
What's the inspiration behind SOM?