mdzaheerjk/Thunderstorm-Forecasting-with-MLFlow-Tracking
Develop a robust thunderstorm forecasting system leveraging machine learning models and MLflow for tracking experiments. This project integrates data preparation, model training, hyperparameter tuning, and deployment to predict thunderstorm occurrences, enhancing weather prediction accuracy and enabling proactive safety measures.
This system helps meteorologists and weather forecasters predict thunderstorms more accurately. It takes in historical weather data and, using machine learning, outputs predictions of thunderstorm occurrences. This enables better public safety alerts and operational planning for those impacted by severe weather.
Use this if you need to improve the precision of your thunderstorm predictions and want a system that learns from past weather patterns.
Not ideal if you need real-time, instantaneous local forecasts based on current conditions without historical data analysis.
Stars
7
Forks
—
Language
—
License
MIT
Category
Last pushed
Jan 27, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mdzaheerjk/Thunderstorm-Forecasting-with-MLFlow-Tracking"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
NVIDIA/earth2studio
Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.
mllam/neural-lam
Research Software for Neural Weather Prediction for Limited Area Modeling
chengtan9907/OpenSTL
OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
NVIDIA/earth2mip
Earth-2 Model Intercomparison Project (MIP) is a python framework that enables climate...
aditya-grover/climate-learn
Source code for ClimateLearn