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This document discusses a study on crop yield prediction using machine learning techniques, specifically deep learning frameworks like TensorFlow and Keras. The research highlights the advantages of using Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks to analyze agricultural data, achieving a prediction accuracy of 93% and reducing yield prediction errors by 65%. The findings suggest that AI-driven predictive analytics can significantly enhance farming decisions and sustaina

Author

aniket190705

Language

EN