Extract screenshots folder to see the images of working project. Extract all the files.

This folder contain the codes and data created during Hackathon '20 for admission and jobs prediction based on demographic location. Hackathon is organised by CHARUSAT University.

Our problem statement: PREDICTION OF ADMISSION & JOBS IN ENGINEERING AND TECHNOLOGY WITH RESPECT TO DEMOGRAPHIC LOCATIONS.

For demonstration purpose, we chose some target areas and used limited number of parameters. We did case study of those areas and got the expected outputs. These results can later be generalised to a very large area, even to the scale of countries, provided we get the required data. The data used in the creating this project is synthetic which was made after a complete experimentation and research of the area. The credibility of data lies in the fact that all the values and parameters chosen are taken from valid sources which includes annual report of colleges and companies, cagr of companies etc. The working of this project depends upon the quality and availibility of data.

We used Android SDK for creating application.

A neural network model is used for the prediction of admission and jobs. LSTM: 4 layers with varying number of neurons GRU: 4 layers with varying number of neurons LINEAR REGRESSION: for admission

The product target two types of user:

1. AICTE/UGC or other granting committees
2. Users and enthusiasts willing to study the trends and see the availibility of jobs at a particular location

The predictions we made are shown in the form of graphs. Due to inavailibility of data, the graphs are the static based on predictions from previous data