SunilRavi7/Water_Quality_Prediction_and_Analysis_using_ML
The project predicts water potability using machine learning, classifying samples as safe or unsafe for drinking. It uses features like pH, hardness, solids, chloramines, sulfate, conductivity, organic carbon, trihalomethanes, and turbidity to enhance prediction accuracy.
No commits in the last 6 months.
Stars
—
Forks
—
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 04, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/SunilRavi7/Water_Quality_Prediction_and_Analysis_using_ML"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
OuyangWenyu/torchhydro
TorchHydro: datasets, and models for watershed hydrological modeling
mhpi/hydrodl2
Repository for MHPI differentiable hydrological models.
confidence-duku/bakaano-hydro
A distributed hydrology-guided neural network model for streamflow prediction
WaterFutures/water-futures-battle
Part of the Battle of Water Networks competition series | WDSA/CCWI 2026, May 18-21, Paphos,...
IBM/Environmental-Intelligence-Suite
IBM Environmental Intelligence Suite