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Weather Prediction
BackpropagationPythonTensorFlowData OversamplingTime Series Analysis
Category
Machine LearningProject Overview
Developed a backpropagation model with oversampling to address imbalanced data, achieving 80%+ accuracy
Detailed Description
This weather prediction system uses neural networks with backpropagation to forecast weather conditions. I identified a significant challenge with imbalanced data, as certain weather patterns were underrepresented in the training set. To solve this, I implemented oversampling techniques that improved model performance by ensuring adequate representation of all weather conditions. The final model achieves over 80% accuracy in predicting various weather patterns based on historical meteorological data, including temperature, humidity, wind speed, and atmospheric pressure.