An interactive web application developed with Streamlit, designed for making predictions using various machine learning models. The app dynamically generates forms and pages from JSON configuration files. ⭐ If you found this helpful, consider starring the repo!
🌟 Is your feature request related to a problem?:
This machine learning based prediction system will predict the total abroad education cost based on various parameters like fees, stream, course type, education , country, location etc. using various machine learning techniques
💡 Describe the solution you'd like:
All in depth data preprocessing ,EDA, feature engineering , different model training and evaluation And at last streamlit based gui for prediction
🔀 Describe alternatives considered:
using different machine learning algorithm and finally training with the one having highest accuracy
To be Mentioned while taking the issue:
What is your participant role? <!-- i want to work on this for both gssoc'24 extended and hacktoberfest
Note:
Please review the project documentation and ensure your code aligns with the project structure.
Please ensure that either the predict.py file includes a properly implemented model_details() function or the notebook contains this function to print a detailed model report. The model will not be accepted without this function in place, as it is essential for generating the necessary model details.
Prefer using a new branch to resolve the issue, as it helps keep the main branch stable and makes it easier to manage and review your changes.
Strictly use the pull request template provided in the repository to create a pull request.
yashasvini121
commented
3 weeks ago
🌟 Is your feature request related to a problem?: This machine learning based prediction system will predict the total abroad education cost based on various parameters like fees, stream, course type, education , country, location etc. using various machine learning techniques
💡 Describe the solution you'd like: All in depth data preprocessing ,EDA, feature engineering , different model training and evaluation And at last streamlit based gui for prediction
🔀 Describe alternatives considered: using different machine learning algorithm and finally training with the one having highest accuracy
To be Mentioned while taking the issue:
Note:
predict.pyfile includes a properly implementedmodel_details()function or the notebook contains this function to print a detailed model report. The model will not be accepted without this function in place, as it is essential for generating the necessary model details.