andrea-gasparini/big-data-weather-forecasting
Big Data weather forecasting, experimenting with logistic regression, SVM and random forest in a distributed setting by using PySpark
This project helps meteorologists and data scientists predict future weather conditions based on historical weather measurements. You input large datasets of past hourly weather data like temperature and humidity for multiple cities, and it outputs predictions of meteorological conditions. This is ideal for researchers or analysts working with extensive weather data.
No commits in the last 6 months.
Use this if you need to analyze vast amounts of historical weather data to forecast future conditions using machine learning in a distributed environment.
Not ideal if you need real-time, ultra-high-resolution forecasts or if your weather data is small enough to be processed on a single machine.
Stars
9
Forks
1
Language
Jupyter Notebook
License
—
Category
Last pushed
Apr 28, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/andrea-gasparini/big-data-weather-forecasting"
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