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🐱🐶 Cats vs. Dogs Classifier 🐶🐱

Welcome to the Cats vs. Dogs Classifier GitHub repository! 🎉

This project focuses on building a robust binary classification model to distinguish between images of cats and dogs. With the proliferation of pet images on social media and the internet, accurately classifying these furry friends has become an exciting challenge in the field of computer vision.

📁 Dataset Source: The dataset used in this project is sourced from Kaggle's "Dogs vs. Cats" competition. It consists of thousands of labeled images of cats and dogs, making it an ideal resource for training and evaluating our classifier. You can find the dataset here.

🔍 Objective: The goal is to develop an efficient and accurate deep learning model that can automatically identify whether an input image contains a cat or a dog.

🛠️ Key Features:

• Utilizes state-of-the-art deep learning techniques for image classification.
• Pre-processing methods to enhance model performance and handle diverse image characteristics.
• Training and evaluation scripts for seamless model development and assessment.
• Easily customizable architecture to experiment with different neural network configurations.
• Documentation and examples to facilitate understanding and usage.