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.