ML-Crate stands as the ultimate hub for a multitude of exciting ML projects, serving as the go-to resource haven for passionate and dedicated ML enthusiasts!ππ« Devfolio URL, https://devfolio.co/projects/mlcrate-98f9
I have run the the model in my local notebook.
I selected the model with best accuracy and exported using pickle.
I have created a separate folder named as the Project Title.
Inside that folder, there are :
Images - To store the required images.
Dataset - To store the dataset or, information/source about the dataset.
Model - To store the machine learning model you've created using the dataset.
Web app - app.py file to run the web app.
Type of change βοΈ
What sort of change have you made:
[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] Code style update (formatting, local variables)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update
How Has This Been Tested? βοΈ
I have tested the air quality prediction app by running the app on Streamlit and verifying the result by testing different inputs .
Checklist: βοΈ
[x] My code follows the guidelines of this project.
[x] I have performed a self-review of my own code.
[x] I have commented my code, particularly wherever it was hard to understand.
[ ] I have made corresponding changes to the documentation.
[x] My changes generate no new warnings.
[ ] I have added things that prove my fix is effective or that my feature works.
[ ] Any dependent changes have been merged and published in downstream modules.
Pull Request for ML-Crate π‘
Issue Title: [Feature Addition]: Web App for Air Quality Prediction
Closes: 596
Describe the add-ons or changes you've made π
I have run the the model in my local notebook. I selected the model with best accuracy and exported using pickle. I have created a separate folder named as the Project Title. Inside that folder, there are : Images - To store the required images. Dataset - To store the dataset or, information/source about the dataset. Model - To store the machine learning model you've created using the dataset. Web app - app.py file to run the web app.
Type of change βοΈ
What sort of change have you made:
How Has This Been Tested? βοΈ
I have tested the air quality prediction app by running the app on Streamlit and verifying the result by testing different inputs .
Checklist: βοΈ