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Developed a neural network model in MATLAB to forecast Apple stock prices using historical data. Applied Gradient Descent and Quasi-Newton optimization methods to train a single hidden-layer feedforward network with a custom activation function. Integrated data preprocessing, feature normalization, and L2 regularization to reduce overfitting.

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