The Practical MLOps book repository points chapter three at chapter six

Chapter 3's source links resolve into the chapter6 directory

The outline is headed `Chapter 3: Machine Learning Deployment In Production`, and the three file links filed under its source heading are all paths into `chapter6/`: a directory called `chapter6`, a `chapter6/multiple-loggers` directory and a `chapter6/simple-logging` directory. The links are written against `blob/master`, too, while the repository's default branch is `main`. Whatever those three directories contain, they are not being presented as chapter 3 material, or if they are, the README has not settled it. Chapter 6 is titled Monitoring and Logging for Machine Learning, and its own source heading is empty. So the deployment chapter borrows the logging chapter's files, and the logging chapter points at nothing. A reader following the outline in order arrives at chapter 6 and finds a blank page where three links should be.

Six chapters have an empty source heading, and three of those still have a directory

Chapters 4, 6, 8, 10, 11 and 12 print a `Source Code Chapter N:` heading and then nothing at all. That is half of a twelve-chapter outline with no attached code, in a repository whose stated purpose is storing code samples. Three of those six chapters have a directory waiting at the top level anyway: `chapter4/`, `chapter10/` and `chapter11/`. Chapters 8 and 12 have no directory at all, and neither does chapter 1 or chapter 9. So the mapping between outline and tree is uneven in both directions, and the direction that matters for a reader is the one where a heading promises files and the tree offers no link to them.

Most chapter links leave the repository and land in another account

Count the outbound targets and the character of the repository changes. Chapter 1 links a multi-cloud GitHub Actions demo, chapter 2 links three more, chapter 5 links an Apple CreateML walkthrough, an FLAML notebook and a model explainability project, chapter 7 links seven items including a Flask Elastic Beanstalk repo, an EKS Fargate tutorial and two AWS certification exam guides, and chapter 9 links four more including GCP from zero and a Kubernetes hello world. All of them sit under `noahgift/`, which is the author's personal account rather than the `paiml` organisation. The nine community recipes do the same with named contributors, from Jason Adams through James Salafatinos and Nikhil Bhargava. Exactly five links in the whole outline resolve to a file inside this repository, and one of those five is the chapter 6 path discussed above.

Two branch names appear in the same set of file links

The default branch is `main`, and two links use it: the Ludwig notebook under chapter 5 and the Excel schedule template under chapter 9, both written as `blob/main`. The three chapter 6 links under chapter 3 are written as `blob/master`. Both forms sit in the same list, a few lines apart, which means the links were not written at one sitting against one convention. Whether the master paths still resolve depends on whether the project ever renamed its branch, and nothing in the repository settles that. It is a small thing to notice, but it is the kind of detail that decides whether a reader clicking through gets the notebook or a 404.

There is no LICENSE file at the top level of a code sample repository

The top level holds `.github/`, eight chapter directories, two notebooks, one spreadsheet and the README. A LICENSE file is not among them, and no license is declared for the repository. For a book this is a strange gap, because the sample code is the part people actually want to reuse. Code samples that accompany a commercial title are usually the most-copied part of a book, and an unlicensed repository gives you nothing to point at when someone asks whether your training pipeline can borrow a logging example. Check the terms on the book's own pages before lifting anything from `chapter6/` or from either notebook.

Two notebooks at the root, and only one of them has a link

The repository's primary language is Jupyter Notebook, and exactly two notebooks sit at the top level: `Ludwig.ipynb` and `Data_Science_With_Covid.ipynb`. The Ludwig notebook is linked from the outline, under the AutoML chapter, as a Ludwig text classification walkthrough. The COVID notebook has no link anywhere in the README. The closest thing to a pointer is a community recipe for a Covid Predictor, and that recipe credits an outside repository rather than the file sitting in this tree. So one of the two notebooks is reachable only by browsing the repository itself, and the community recipe list would have you looking somewhere else entirely for the same subject.

The first screen of the README is a course catalogue

The opening lines advertise a Hugging Face specialisation on Coursera, a Master GenAI Engineering course, a professional Rust course, an AWS AI and analytics course, a production GenAI course and a Rust DevOps course. Then a career section, a Fortune 500 claim, and a line offering end-to-end ML engineering from industry veterans. The book's own description does not arrive until after all of that, and it is one sentence: the repository is where code samples for Practical MLOps are stored. The closing section points at five Duke Coursera courses, an edX note and a Discord invite. Read as a landing page this works. Read as an index of a book's source code, the proportion pointing at the code is small.

The outline calls itself tentative and keeps a strikethrough

The heading above the chapter list reads `Tentative Outline`. The chapter 3 title carries a strikethrough over the word `Strategies`, so the final title of that chapter is unclear from the page alone. The community section explains its own status directly: many of those recipes may be included in the book if timing works out. Given all that, the repository is better understood as a workspace than as a finished companion to a published table of contents. The book itself is reachable through the O'Reilly library view and through a purchase link on Amazon, and neither of those is a file in this tree.

Editorial conclusion

Treat this repository as a bookmark file rather than a codebase. It is worth reading if you want the author's index of AWS, AutoML and GCP walkthroughs, and it is worth fixing up if you are the kind of person who navigates by directory name, because chapter3/ exists but the chapter 3 links resolve into chapter6/, chap05/ breaks the naming pattern of every other directory, and there is no LICENSE file at the top level to tell you what you may reuse. The last push on the default branch was 2026-03-26 and the repository has never cut a GitHub release. If you want the book text itself, none of it is here.

Frequently asked questions

Official sources

1. Issues
2. paiml/practical-mlops-book on GitHub
3. README