Abstract
This research explores the development and application of artificial intelligence (AI) models in Python for plant disease classification. Using a large training dataset with over 50,000 images representing various plant conditions, the study highlights the effectiveness of AI and computer vision by achieving approximately 86% accuracy in correctly identifying the plant disease. It demonstrates a balanced approach to maintaining accuracy while avoiding overfitting, underscoring AI's potential in agriculture.
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