🐱 Cat-and-Dog Image Classifier This repository contains my solution to the Cat and Dog Image Classifier project, completed as part of the freeCodeCamp Machine Learning curriculum. The objective of this project was to build a neural network model capable of classifying images as either cats or dogs using TensorFlow and Keras.

🧠 Model Summary Architecture: Convolutional Neural Network (CNN)

Frameworks: TensorFlow, Keras

Dataset: Cats vs Dogs dataset from Microsoft (via TensorFlow Datasets)

Preprocessing: Image resizing, normalization, and data augmentation

Metrics: Accuracy, Loss

🚀 Features Loads and preprocesses a real-world image dataset

Builds and trains a CNN for binary image classification

Uses data augmentation to improve model generalization

Evaluates performance on validation/test data

Includes plots of training vs validation accuracy/loss

💡 Make sure you have TensorFlow installed.

🏆 Project Goal This was an assignment project for the freeCodeCamp Machine Learning certification. The main objective was to gain hands-on experience in image classification using convolutional neural networks.

📚 Acknowledgments Thanks to freeCodeCamp for the excellent learning material and project structure. Dataset courtesy of Microsoft Research.