Conducted research to evaluate the ability of neural networks to understand cognition using MATLAB.
Implemented a back-propagation algorithm on cancer datasets to classify tumors as benign or malignant, achieving insights into neural network limitations in representing cognition.
Built and trained neural network models to analyze real-world datasets, utilizing MATLAB’s Neural Network Toolbox to evaluate classification accuracy and identify patterns in false positives and false negatives.
Developed a back-propagation network in Excel to solve Exclusive OR (XOR) problems, demonstrating proficiency in algorithm implementation and debugging.
Critically analyzed philosophical arguments about neural networks and cognition, integrating computational insights with cognitive theories.
Presented findings on the limitations of neural networks in cognitive representation, contributing to interdisciplinary discussions on AI and human cognition.
