A Machine learning model to predict the efficiency of employees in workspace. The prediction is based on 11 parameters namely- Experience(yrs),TaskAssigned,TaskCompleted,DeadlinesMet,DeadlinesMissed,number of EOM(Employee of the month) ,EOM points (agg) ,EOY(points),Manager Score,Holidays Taken,Number of hours overtime.
The ML model is based on neural network using Data Envelopment Analysis (DEA) which is based on Linear Programming. The user interactions are handled from react based interactive user interface.
Dependencies installation script ( Unix )
sudo apt install python3 pip3 python3-venv
git clone --recursive git@github.com:ShisuiMadara/HackIISC.git
cd HackIISC
python3 -m venv venv
source venv/bin/activate
pip install -r ./requirements.txt- Python
- pyDEA
- React.js
- ReCharts
- MUI
- SQLite
- Flask
The web application has a highly interactive user interface.
- The robust backend handles all the computations, thus all the company has to do is to CLICK !!
- The performance is presented in the form of interactive charts.
- Maintaining a curated resource list on how to fill performance reports and how to grow as a developer.