Agmar LSTM Model is a project that implements a Long Short-Term Memory (LSTM) model to predict the modal price of agricultural commodities. The model utilizes historical data to forecast future prices, aiding in decision-making for farmers and traders.
Analyzed United States Department of Agriculture Census data using SAS and Python to explore how agricultural commodities prices in North Carolina have changed from 2012 to 2017 and what factors drive the change
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