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.

• 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.

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.

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.

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