Toolkit

The stack I default to.

The tools I reach for, and roughly why. Nothing exotic. I care more about shipping something that works than about the stack it runs on.

Languages

  • Python for almost everything: ML, data, backends, automation.
  • JavaScript and TypeScript for the web, including this site.
  • SQL whenever the data lives in a database.

ML and data

  • PyTorch and TensorFlow for models; scikit-learn for classical work.
  • LangChain for retrieval pipelines; Sentence-Transformers with a Chroma vector store for embeddings and similarity search.
  • Pandas and NumPy for wrangling; Matplotlib, Seaborn, and Plotly for plots.

Visualization

  • Power BI and Tableau for dashboards.
  • Streamlit when a project just needs a quick interactive UI.

Tooling

  • Git and GitHub, with GitHub Actions for automation. It's what runs the class-recording pipeline I built at ISL.
  • VS Code and a terminal-heavy workflow for everything else.

Certifications

The courses that stuck, and where I put them to work.

Contact

The twin answers questions; the human answers emails.