The projects covered in this book can be considered bite-sized projects. They can be completed within a day or two. A real project will often take months. They require a combination of machine learning expertise, engineering expertise, and DevOps expertise. It would not quite be feasible to write about such projects without spanning multiple chapters while keeping the same level of detail. In fact, as can be witnessed by the progression of this book, as projects get more complex, the level of detail drops. In fact, the last two chapters are pretty thin.
All said and done, we've achieved quite a bit in this book. However, there is quite a bit we have not covered. This is owing to my own personal lack of expertise in some other fields in machine learning. In the introductory chapter, I noted that there are multiple classification schemes for machine learning...