GitHub - ttudii/Stock-Price-Prediction: 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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324AA_Cinteza_Tudor-Andrei.pdf		324AA_Cinteza_Tudor-Andrei.pdf
AAPL.csv		AAPL.csv
document.pdf		document.pdf
unconstrained_optimization_problem_deep_learning.m		unconstrained_optimization_problem_deep_learning.m

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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.