Irrigation Need Prediction using Deep Neural Network
تفاصيل العمل
Built a Deep Neural Network using TensorFlow/Keras to predict irrigation needs (Low, Medium, High) from environmental and soil data, achieving high performance in a Kaggle competition. Applied advanced preprocessing, feature engineering, and class balancing to enhance model accuracy and generalization. Ranked among competition winners using Stratified K-Fold Cross Validation and robust training strategies for reliable predictions.
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