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Uses

The tools I work with every day

An honest inventory of the stack I use to build end-to-end machine learning systems: from data to model, from model to production, and from production to monitoring.

Language and machine learning

  • Python
  • scikit-learn
  • XGBoost
  • LightGBM
  • PyTorch
  • Transformers · HuggingFace
  • pandas · NumPy · polars

LLM applications

  • RAG
  • LangChain
  • OpenAI API
  • tiktoken
  • Sentence Transformers

Serving and infrastructure

  • FastAPI
  • Pydantic
  • uvicorn
  • Docker
  • GitHub Actions · CI/CD

Monitoring and data

  • Prometheus
  • Grafana
  • PostgreSQL
  • SQL
  • Parquet · Polars

Working environment

  • Linux
  • Neovim
  • VS Code
  • git
  • uv
  • ruff
  • tmux
hola@jmwebsoluciones.com