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This AI model addresses the critical challenges the Small-Scale fisheries face in the Gulf of California, a pivotal region for Mexico's fisheries production and biodiversity. Amid climate change's backdrop, these tools leverage Deep Learning techniques to forecast fish catch volumes, contributing to sustainable resource management and informed decision-making. The goal is to employ deep learning models to explore the complex dynamics between oceanic conditions and catch volumes, thereby aiding in the sustainable management of fisheries in the Northern Gulf of California. This involves analyzing the intricate relationships and predicting future catch volumes amidst evolving climate patterns.
