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Leverage Metaflow, PyTorch, AWS S3, Elasticsearch, FastAPI and Docker to create a production-ready facial recognition solution. It demonstrates the practical use of deep metric learning to recognize previously unseen faces without prior training.

License: MIT License

Makefile 1.10% Python 97.38% Shell 1.52%
artificial-intelligence aws face-recognition facial-recognition fastapi machine-learning-engineering metaflow metric-learning triplet-loss approximate-nearest-neighbor-search

full-stack-deep-facial-recognition's Introduction

Hey there! 👋

I'm Gabriel Tardochi Salles, an experienced Machine Learning Engineer passionate about efficiently delivering intelligent systems.

Welcome to my GitHub profile!

  • 🌱 Born in: São Paulo, SP, Brazil
  • 💼 Currently working on: ML Engineering at Itaú
  • ☁️ Cloud certifications: AWS Machine Learning – Specialty
  • 🚀 Currently exploring: Advanced ML deployment techniques and open-source
  • 💡 Passionate about: ML Engineering, MLOps, Natural Language Processing/Understanding and Computer Vision
  • 💬 Ask me about: ML algorithms/architectures, model deployment, or just chat about tech!

I also (try to) write about ML-related topics on Medium ✍️

Get in Touch

Let's connect and build awesome things together! 🤖✨

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