HoneB – DL based H1B visa prediction App

The Problem Statement: The number of people moving abroad in pursuit of higher-paying professions, reputable education, and modern surroundings have been increasing drastically each year. As a consequence the application for H1B visa have also increased in number drastically. Given the volume of applications, the likelihood of a visa being rejected is very high. Numerous American employers want to hire qualified foreign workers each year. Thousands of applicants still receive H-1B visa denials even though many are successful in bringing their new staff to the United States.

The Solution Application: The Flutter based cross platform mobile application uses the Django rest framework for its backend access where there is a Deep neural network based prediction model to predict the acceptance of H1B visa for the application user

Deep Neural Network:
Number of Hidden Layers:5
Activation Function for Hidden Layers:Relu
Number of Output Layer:1
Activation Function for Output Layer:Sigmoid
Optimizer:Adam
Loss Function:Binary crossentropy

The accuracy we got for deep neural network is 98%.

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