A neural network model can be used effectively in predicting training accuracy using machine learning. Based on the comparison of forward and backward neural networks, coded to communicate their output in the requisite manner using machine language is the basis of the present study. With the help of students' background information, to predict the Grade Point Average (GPA) of 580 engineering students based on various parameters, including mental health. The study is based on the Boruta algorithm and the random forest methods for data preparation in the matrices (12 * 2 = 24) of single-layered, multiple-layers, and forward and reverse algorithms adopted to test the prediction and accuracy of the grade point average by analyzing histograms, confusion matrices, and regression analysis. This study suggests the best model for predictions with the help of artificial neuron network that has roughly half the number of single layers and with three hidden layers.
Community health diagnosis is a comprehensive assessment of health status of the community in relation to its social, physical and biological environment. The purpose of community health diagnosis is to define existing problems, determine available resources and set priorities for planning, implementing and evaluation health action, by and for the community. A cross sectional descriptive study was done at Dhampus VDC from 1 Sept 2016 AD (16th Bhadra, 2073 BS) to 16 Sept 2016 AD (31st Bhadra, 2073). The data was collected by questionnaires, anthropometric measurements, interviews and secondary data. The community health diagnosis field visit gave us the opportunity to build our team spirit and taught us the arts of problem solving. It taught us the importance of correct conduct and building a good rapport with the people who were unfamiliar to us. J-GMC-N | Volume 11 | Issue 01 | January-June 2018, Page: 71-76
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