Detection of Mental Health using machine learning NLP This is an end to end implementation of detecting mental health from textual data using machine learning and NLP This project has been deployed in streamlit Open source library Streamlit is a popular open-source framework for building and deploying machine learning models. To use Streamlit to deploy your machine learning model, you can follow these steps:
Install Streamlit using pip install streamlit
Import the necessary libraries and classes, such as numpy and sklearn, as well as your trained machine learning model.
Use Streamlit's built-in functions to create a user interface for your model.
This can include text boxes for user input, buttons to trigger model predictions, and visualizations to display the results of the predictions.
Use the st.write function to print the output of your model to the screen.
Test your app locally by running streamlit run app.py, where app.py is the name of your Python file.
Deploy your app to a web server or hosting platform, such as Heroku or AWS Elastic Beanstalk, to make it accessible to others.
It is also possible to use Streamlit to train and fine-tune machine learning models, but this is not its primary focus.
Instead, Streamlit is designed to make it easy to build user interfaces for existing models and to quickly deploy them for use in production.
