What it does This repo hosts the complete text of Andrew Ng’s Machine Learning Yearning — a book about the practical politics of shipping ML systems — sliced into 13 chapter-range PDFs plus one consolidated file. It’s essentially a well-organized file cabinet: click, download, read offline.

The interesting bit The slicing itself is the product. Ng’s original is free but monolithic; this turns it into linkable, shareable chunks. The dev/test set advice the book covers has aged into relevance as datasets ballooned — the repo just makes that advice easier to point teammates at.

Key highlights

• Full book plus 13 part-PDFs (Ch. 1–58)
• Covers team alignment, dev/test set construction, and modern dataset sizing
• Direct PDF links — no build step, no wrapper code
• Free license (per repo badge)
• 1.1k stars suggests decent discoverability

Caveats

• The GitHub issues badge actually links to a different repo (travis-ci-with-github), which is either a copy-paste error or a cry for help
• No source text, no search, no annotations — pure file hosting
• Last meaningful update unclear; README is static

Verdict Grab this if you want Ng’s book in bite-sized PDFs for offline reading or team handouts. Skip it if you were hoping for code, searchable HTML, or commentary — this is a mirror, not a remix.