Halfmarathon Estimator App
Date of creation: 2024-10-20
Project description
The aim of the project was to create an application that would use a regression algorithm to train models and would be able to predict (based on previously trained data) the time in which a user would run a half marathon - by providing specific data.
Main functionalities
- allowing the user to enter data freely (without any appropriate conversion of the record) -> the LLM model used extracts data from the user into a JSON structure and prepares it for use by the regression model
- simple functionality allows for the final estimation of the time to run a half marathon - using the trained best regression model
- the LLM model is connected to Langfuse to track the model's life cycle
ML model training
I used PyCaret tools and I have included the implementation in a notebook ready for download:
Download Notebook: Model training
Download Notebook: Model training
Skills
- Python
- PyCaret
- Machine Learning
- Langfuse
- OpenAI
- Streamlit
- Pandas
- Instructor
- Pydantic
- Dotenv
Sample photos
Application testing
The application has been deployed on the Streamlit Community App and is available for public use.
To use the application you need your OpenAI API Key.
To use the application you need your OpenAI API Key.