Develop an AI-based image classification system using CNN and transfer learning. The project includes data preprocessing, model training, fine-tuning, evaluation with precision, recall, and F1-score, and testing.

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.

Regularization is a crucial technique in machine learning that helps to prevent overfitting. Overfitting occurs when a model becomes too complex and learns the training data so well that it fails to generalize to new, unseen data.