📝 TensorFlow Cats vs. Dogs Image Classification

📘 Introduction

The TensorFlow Cats vs. Dogs Classification project showcases the application of convolutional neural networks (CNNs) for distinguishing between images of cats and dogs. Using the TensorFlow framework, this project provides a complete pipeline for training, validating, and testing a model to achieve high accuracy in image classification tasks.

✨ Key Features

• Convolutional Neural Network: Optimized CNN architecture for efficient feature extraction.
• Extensive Dataset: Trained on a large labeled dataset of cat and dog images.
• Model Evaluation: Comprehensive evaluation metrics to monitor performance.
• Transfer Learning: Uses pre-trained models to enhance performance and reduce training time.
• User-Friendly Implementation: Clear and modular codebase for easy understanding and modification.

🤝 Contributing

The TensorFlow Cats vs. Dogs Classification project is open-source, and contributions are welcome. Feel free to fork the repository, make your changes, and submit a pull request.

📞 Contact

If you have any questions or need further assistance, you can contact the project maintainer:

• Name: Matias Vallejos
• 🌐 matiasvallejos.com Feel free to reach out for inquiries or additional information about the project.

📄 License

This project is open source and available under the MIT License.