industry-machine-learning

Why we included this project

Data scientists and ML engineers who want a map of how machine learning actually gets applied inside different sectors will save themselves weeks of digging through scattered GitHub repositories with this index. It groups notebooks and libraries by industry, covering agriculture, banking, healthcare, legal, and manufacturing, and keeps the subtopics the original authors created, such as fraud detection, risk, and text analysis. Each entry points to code you can study, adapt, or run to see how a technique was used on a real business problem. The maintainer also runs a deprecation policy for stale projects, so the list stays usable instead of collecting dead links, and the repo documents how to contribute, which keeps it growing through pull requests. For someone exploring an ML career, teaching an applied course, or starting work in a vertical they have not touched before, this is a practical starting point rather than a static collection.