Model CNN for weather prediction

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This presentation focuses on leveraging advanced AI methods like 1D CNNs for weather prediction. It outlines the technical process of weather data preprocessing, feature engineering, and model development using Conv1D layers, dropout, and Adam optimization. Key metrics like MSE, MAE, and R² are discussed alongside visualization techniques to evaluate performance. The session highlights challenges in weather forecasting and explores future enhancements, such as integrating LSTM features,...

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