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eugeneyan/applied-ml

eugeneyan / applied-ml

Dev Agents & ProgramsOtherMIT

Papers & tech blogs by companies sharing their work on data science & machine learning in production.

30.5kstars
4kforks
12open issues
2024-07-18last pushed
MITlicense

What it is, and how people use it

Papers & tech blogs by companies sharing their work on data science & machine learning in production. It sits on the Dev Agents & Programs shelf of the catalog, maintained by @eugeneyan.

✓Drop-in for Claude Code, Codex CLI and Cursor - install and it just runs.
✓Read the SKILL.md / README first; most setups are one command from the docs.
✓Teams use it to standardise how agents behave across every repo in the org.
applied-data-scienceapplied-machine-learningcomputer-visiondata-discoverydata-engineering

Why builders keep it installedDev Agents & Programs benefits

Day-one leverage

These CLIs and dashboards solve one job well and install with a single command. Value shows up in the first hour, not after a config weekend.

Composes with your agent

Most of them ship an MCP server, skill or hooks - so the same tool you use manually becomes an action your agent can call safely.

Built under real workloads

Star counts here track repos people actually run daily: the issue history shows bug classes fixed under production pressure, not demo-week polish.

Free and open source

Every tool on this page ships under an open license and can be self-hosted. Your usage data and your configs stay yours.

Contributorsloading from GitHub…

Languagesestimated from snapshot

  • Other 69.0%
  • TypeScript 19.0%
  • Shell 12.0%

Community pulsesnapshot ratios, normalized

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