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I am quite surprised there is no discussion here. The book actually gives a nice overview of practical Software Engineering principles applied to ML Engineering

I am quite surprised there is no discussion here. The book actually gives a nice overview of practical Software Engineering principles applied to ML Engineering and hence of use to regular Programmers moving to ML from other domains. I personally found it quite useful to understand the practices employed in ML Engineering and how it is different from "normal" programming which is where i come from. Part II titled "Best Practices for Machine Learning Pipelines" and starting from chapter 5 is where the meat lies.

nerdponx 2y ago
It's new to me! It certainly looks good, or at least like something that could be increasingly useful to an increasingly large group of people. But it's a whole book and I have only a few minutes' break to check HN, so I can't evaluate it for quality until I've had a chance to read it (and I definitely will, because it looks useful to me). I assume, being new, few other people have experience with it to comment. And fortunately whenever actual math and code show up, the AI maximalist/doomer blabbermouths tend to stay away.
- dijksterhuis 2y ago
  I’ve had a skim through bits. It look good and thorough for ML Engineer / Data Engineer stuff. Definitely recommend checking it out yourself, even if it’s only to bookmark for sending onto others as a reference manual. > And fortunately whenever actual math and code show up, the AI maximalist/doomer blabbermouths tend to stay away. When I see something mentioning machine learning + engineering, I’m interested. When I see AI mentioned I automatically discount it as marketing fluff. It’s worked well as a filter for almost 10 years now (the last hype cycle).
FrustratedMonky 2y ago
came here to ask. Since I don't know enough about ML to know if this is good, is it as good as the original 'Pragmatic Programmer', to justify the title? A lot of books rif off a poplar name, so asking if this lives up to it, and worth more time investment to read it.
- rramadass 2y ago
  https://news.ycombinator.com/item?id=41563211 https://news.ycombinator.com/item?id=41563211 It is a overview of practical issues book and hence an easy read.

nerdponx 2y ago

It's new to me! It certainly looks good, or at least like something that could be increasingly useful to an increasingly large group of people. But it's a whole book and I have only a few minutes' break to check HN, so I can't evaluate it for quality until I've had a chance to read it (and I definitely will, because it looks useful to me). I assume, being new, few other people have experience with it to comment. And fortunately whenever actual math and code show up, the AI maximalist/doomer blabbermouths tend to stay away.

dijksterhuis 2y ago
I’ve had a skim through bits. It look good and thorough for ML Engineer / Data Engineer stuff. Definitely recommend checking it out yourself, even if it’s only to bookmark for sending onto others as a reference manual. > And fortunately whenever actual math and code show up, the AI maximalist/doomer blabbermouths tend to stay away. When I see something mentioning machine learning + engineering, I’m interested. When I see AI mentioned I automatically discount it as marketing fluff. It’s worked well as a filter for almost 10 years now (the last hype cycle).

FrustratedMonky 2y ago

came here to ask. Since I don't know enough about ML to know if this is good, is it as good as the original 'Pragmatic Programmer', to justify the title? A lot of books rif off a poplar name, so asking if this lives up to it, and worth more time investment to read it.

rramadass 2y ago
https://news.ycombinator.com/item?id=41563211 https://news.ycombinator.com/item?id=41563211 It is a overview of practical issues book and hence an easy read.