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Natural Language Processing in Action: NLP from an ML Engineer perspective

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Hi Hobson, Hannes, and Cole,

Congratulations on completing the Book and wish you good luck !!

Just reviewed the table of contents from   .  It feels complete from a Datascientist/Model developer perspective .

Some of the Questions in my mind , hope to get insights on these topics after reading in the book ,

1.  As an ML engineer a lot of times we struggle operationalizing an ML model from prototyping to production - Any Recommendations and best practices (version control, re-usability of a trained model )
2.  How good the AutoML tools solve the  NLP challenges?
3.  What are some of the Cloud Native NLP solutions, without needing to code a lot to rapidly prototype something?
4.  What are your recommendations in terms of running NLP at scale ?

Suresh Sethuramaswamy
It is sorta covered in the JavaRanch Style Guide.
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