A full stack application that can accurately calculate employee wellbeing and predict future trends using machine learning.
https://devpost.com/software/well-track
We have identified a number of metrics that can help in accurately understanding the wellness of an employee which ranges from professional details to personal details. We have curated around 30 metrics that will give us a deep insight of the employees overall wellbeing and provide a wholistic wellbeing score.
We will be using various machine learning models to effectively analyse the employee data. We have used feed forward neural networks to accurately calculate the weights of each parameter/metric and an LSTM model to give a precise predicion of future wellbeing scores.
We have a sentimental analysis feature which will provide additional information about the mental and social wellbeing of an employee. We are using Twitter to analyse an employees tweets and provide a mood analysis.
The metrics collected will provide two fold information that will aid in creating strategies for wellness programs as manager-employe compatability and employee-employee compatability along with their wellness levels will be accurately shown through a number of graphs.
Run ng serve for a dev server. Navigate to http://localhost:4200/. The app will automatically reload if you change any of the source files.
Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|guard|interface|enum|module.
Run ng build to build the project. The build artifacts will be stored in the dist/ directory. Use the --prod flag for a production build.
Run ng test to execute the unit tests via Karma.
Run ng e2e to execute the end-to-end tests via Protractor.
To get more help on the Angular CLI use ng help or go check out the Angular CLI Overview and Command Reference page.