Project: Cats or Dogs using CNN with VGG16 + DVC

✨ Project information:

This ML project involves binary classification of dogs and cats using transfer learning with VGG-16 architecture. The goal is to classify images of dogs and cats with about 12,500 training samples in each folder. The project uses DVC (data version control) for managing data. It is built on a microservices architecture and is an end-to-end project. The dataset can be downloaded from this link.

📚 Libraries used :

• Tensorflow
• Keras
• DVC

🚀 Project structure:

🐨 DagsHub Data Pipeline

Complete Project Data Pipeline is available at DagsHub Data Pipeline

🔥 Technologies Used:

1. Python 
2. shell scripting 
3. aws cloud Provider 
4. DVC

🔌 Infrastructure:

1. AWS S3
2. GitHub
3. DaghsHub

👷 Initial Setup:

conda create --prefix ./env python=3.9
conda activate ./env 
pip install -r requirements.txt
dvc init

Conclusion

This project is production ready to be used for the similar use cases and it will provide the automated and orchesrated production ready pipelines(Training & Serving)

Thanks for taking a look at this project. If you find it valuable, kindly rate it by clicking the star icon. Your support is highly appreciated! 😊🙏⭐

📃 License

MIT license © My Website website
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