Lindiwe-22/Strait-of-Hormuz-Crisis-2026
Data-driven intelligence analysis of the 2026 US-Iran War. Investigating how the Strait of Hormuz closure disrupted global oil prices across 14 countries and forecasting the impact on maritime trade volumes using World Bank data, ML modelling and 3-scenario forecasting.
Stars
—
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
Mar 22, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Lindiwe-22/Strait-of-Hormuz-Crisis-2026"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
samirsaci/ml-forecast-features-eng
Machine Learning for Retail Sales Forecasting — Features Engineering
georgeguimaraes/soothsayer
Elixir library for time series forecasting, inspired by Facebook's Prophet and NeuralProphet
Pradnya1208/Time-series-forecasting-using-Deep-Learning
The goal of this notebook is to implement and compare different approaches to predict ...
AstraZeneca/judgyprophet
Forecasting for knowable future events using Bayesian informative priors (forecasting with...
DSkapinakis/sales-time-series-forecasting-ml-models
Sales Time Series Forecasting using Machine Learning Techniques (Random Forest, XGBoost, Stacked...