Comparative study of various training algorithms of artificial neural network

The idea of creating intelligent system has fascinated us with the advent of computer. The artificial neural network is a methodology for the development of intelligent system which can emulate as humans. Increasingly, new algorithms are researched for better efficiency and accuracy. Thereby, this paper examines the performance of different training algorithms for artificial neural network in the feedforward backpropagation architecture. The training algorithms are designed and executed on MATLAB R2017a for the analysis. The various training algorithms are analyzed to find the accuracy level between desired and actual results. The analysis is executed on house price prediction dataset from Kaggle.