This repository implements a 3-layer neural network with L2 and Dropout regularization using Python and NumPy. It focuses on reducing overfitting and improving generalization. The project includes forward/backward propagation, cost functions, and decision boundary visualization. Inspired by the Deep Learning Specialization from deeplearning.ai.
deep-learning gradient-descent l2-regularization performance-optimization model-training regularization-techniques neural-network-architecture overfitting-prevention dropout-regularization
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Updated
Sep 12, 2024 - Jupyter Notebook