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This project leverages LSTM networks, a type of RNN, to accurately predict fruit and vegetable prices by analyzing a comprehensive dataset, utilizing a refined model adept at navigating the complexities and patterns within agricultural market data.
Our Economic Forecasting Model leverages Genetic Algorithms and Random Forests to provide farmers, policymakers, and businesses with cutting-edge insights for informed, profitable decisions in the ever-changing world of agriculture.
This repository contains an Inflation Predictor ML Project using Flask. The project aims to predict the inflation rate based on economic indicators such as GDP and the unemployment rate.
This repository hosts a Jupyter Notebook designed for financial data analysis. It provides tools and examples for analyzing market trends, investment opportunities, or financial forecasts using Python.