cats-dogs-cnn-classification

Project: Cats vs Dogs Image Classification using CNN

This project focuses on building a deep learning model to classify images of cats and dogs using Convolutional Neural Networks (CNN). The model is trained to automatically extract important features such as shapes, textures, and patterns from images to accurately distinguish between the two classes.

The project includes the full pipeline of a machine learning solution, starting from data preprocessing and image augmentation, to model building, training, and evaluation.

Key Features:

* Image preprocessing and normalization

* Data augmentation to improve model performance

* CNN architecture for feature extraction and classification

* Model training and evaluation using accuracy metrics

Technologies Used:

Python, TensorFlow/Keras, NumPy, Matplotlib

This project demonstrates practical experience in computer vision and deep learning, applying CNN models to solve real-world image classification problems.