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rafamartinezquiles/README.md

Hello, I'm Rafael Martínez Quiles


About me

I build real-time ML and computer vision systems, from credit decision engines to production-grade data platforms.

Focus What I Did Impact
ML Decision Engines Designed and deployed credit risk pipelines with explainability (SHAP, scorecards). Reduced loan decision times from ~90 days to < 5 minutes.
Computer Vision Built YOLO-based systems (v8/v9), OCR and tracking for real-time applications. Reached ≈95% accuracy and improved latency by 20%+ in production.
Innovation & Hackathons Competed on applied AI solutions and rapid prototyping. 2nd place in a Google hackathon.
Data Platforms Designed data stacks with Python, SQL, dbt and Airflow on cloud. Delivered reliable pipelines on AWS, GCP & Azure.

Tech I Work With


Connect with me

   


GitHub Stats

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  1. yolov8-bib-recognition yolov8-bib-recognition Public

    Using machine learning algorithms, including Ultralytics, Torch, Tensorflow, OpenCV and NIVIDIA's CUDA to detect numbers on racing bibs found in natural image scene.

    Python 2

  2. yolov9-applications-showcase yolov9-applications-showcase Public

    Using YOLOv9 along with cutting-edge machine learning frameworks such as Ultralytics, PyTorch, TensorFlow, and OpenCV, and utilizing NVIDIA's CUDA for accelerated computing, to explore various appl…

    Python 1

  3. auto-data-agent auto-data-agent Public

    AutoDataAgent is a smart system that automates data analysis, from loading your data to creating detailed reports. It’s built to save time, reduce manual work, and make analysis easier with the hel…

    Jupyter Notebook 1