Another fun book review!
Shifa Ansari and Packt were kind enough to send me a copy of Angelica Lo Duca's 'Comet for Data Science' recently. I've been making my way through it and deep diving into the bits I'm particularly keen on. I think Comet is a great tool and a nice piece of the MLOps stack.
- Lots of detail, really helpful in reading through the examples
- Has some nice touches like the treatment of feature engineering steps in pipelines as their own 'models' you should version and track (I'm stealing this!).
- Chapter 1-5 are really great for classic data science workflows, including covering how Comet can help with those presentations on model performance. Chapter 5 is titled 'Building a narrative in Comet', which is really helpful.
- Chapters 6 and 7 have some really good sections on DevOps, MLOps and how you can use Comet with CI/CD processes in GitLab (I am also stealing this!). Also an introduction to Kubernetes which was great to see. To be honest these were my favourite chapters, lots of great stuff in here. Very good chapters for ML and MLOps engineers.
- Chapters 8-11 have nice worked through examples to bring things to life, including examples with NLP and deep learning models.
Some other points
The way the chapters are split out (as I described above) does mean that if you are not a pure data scientist, you may not get much from the first parts of the book. Not a bad thing, just something to be aware of.Taken together, I thought it was an extremely useful book to have on the shelf.
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