• Yagyanath Rimal

This review paper primarily discusses on neural network machine learning techniques for large data analysis using r programming. Although there is large gap between analysis of research data when there were large set of in associative variables. This paper tries to explore the analysis of predicative modeling procedures steps of large data sets were explained sufficiently to reach conclusion. Its purpose is to explain the simplest way of neural network analysis whose data structure were in scattered using R software whose outputs were sufficiently summarized with various intermediate output and graphical interpretation to get conclusion with example bostonhousing datasets. Therefore, this paper presents easiest way of neural network analysis when data sets with large dimensions and its strengths for data analysis using R programming

Hidden Neuron, Neural Network, over fitted Data, Rectified Linear Unit, Multi-Layer Perceptron

"Neural Network Machine Learning Techniques for Large Noisy Data Prediction using R Programming", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.97-102, May-2019, Available :http://www.jetir.org/papers/JETIRBW06019.pdf

"Neural Network Machine Learning Techniques for Large Noisy Data Prediction using R Programming", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp97-102, May-2019, Available at : http://www.jetir.org/papers/JETIRBW06019.pdf