• Monica
• Mohammad Aasim
• Akash Bhardwaj
• Ajit Kumar Sharma
• Pinku Nath

Abstract: Band gap is a simple but very important material property for screening of materials for various electronic application purposes. Because of imitated availability of band gap values machine learning is a tool to predict the same for newly discovered materials. Here in this article we have provided a very basic principles of least square based methodologies and reviewed the recent work that have been performed for predicting band-gap using machine learning methods.

"Gentle introduction to least square based machine learning techniques and their applications in predicting band gaps", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.103-107, November 2018, Available :http://www.jetir.org/papers/JETIRDS06015.pdf

"Gentle introduction to least square based machine learning techniques and their applications in predicting band gaps", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp103-107, November 2018, Available at : http://www.jetir.org/papers/JETIRDS06015.pdf