machine-learning-yearning-cn

Why we included this project

Andrew Ng's Machine Learning Yearning, in this Simplified Chinese translation, is a field guide to the decisions that separate working ML projects from stalled ones. It skips algorithm theory and instead walks through how to split data into train, dev, and test sets, where to focus error analysis, how to handle cases where training data and production data drift apart, and when adding data beats tuning the model. Engineers and managers starting an applied ML effort will find it a compact reference for judgment calls that courses rarely cover. The translation is hosted as web pages and maintained through a public issue tracker and pull requests, so it reads well online and is easy for readers to suggest corrections to.