ndolobofelo-sketch/Botswana-Food-Inflation-Forecasting-AI

AI-powered food inflation forecasting system using machine learning and LSTM deep learning models for Botswana. \# 🇧🇼 Botswana Food Inflation Forecasting Challenge \## AI-Driven Food Price Inflation Forecasting System Using Economic, Commodity, and Human Capital Indicators \### VenturePulse: Food Price Inflation Forecasting Challenge \### Deep Learning IndabaX Botswana 2026 Hackathon \--- \# 1. Project Overview Food price inflation is one of the most important economic challenges affecting households, businesses, and governments. Accurate forecasting of food inflation enables better policy decisions, improved supply chain planning, and stronger food security strategies. This project develops an Artificial Intelligence-powered forecasting system to predict Botswana food inflation by integrating multiple economic and global indicators, including: \- Food price indices \- Human Capital Project indicators \- Baltic Dry Index shipping activity \- Brent crude oil prices \- Botswana policy interest rates \- Historical inflation trends The objective is to build a robust forecasting framework capable of identifying inflation patterns, understanding economic drivers, and generating accurate future food inflation predictions. \--- \# 2. Motivation and National Importance 🇧🇼 Botswana, like many economies, is exposed to external factors influencing food prices, including: \- International commodity price changes \- Global transportation costs \- Energy price fluctuations \- Monetary policy decisions \- Supply chain disruptions \- Climate-related pressures Food inflation directly affects: \- Household purchasing power \- Food affordability \- Economic stability \- Government planning \- Social welfare programs This project provides an evidence-based AI forecasting approach to support proactive decision-making and improve resilience against future food price shocks. \--- \# 3. Global Relevance 🌍 Food inflation is a global challenge affecting both developing and developed economies. The developed forecasting framework de …