This is a video from the Data Science fwdays'20 online conference, that was held on August 15, 2020.
Description of the discussion:
This is a friendly and not too formal discussion – let’s exchange thoughts and talk. From the perspective of building NLP products, let’s touch on how different aspects were affected in practice or whether they are likely to be affected in the near future:
- Building and productizing NLP models
- Time/effort to find a suitable approach (research)
- Time/effort to build something workable (PoC)
- Time/effort to make it ready for users
- Engineering/science roles and how things they do have changed
- What barriers are still there to overcome for NLP to be broadly available, especially from the application side
Moderator:
Dmitry Unkovsky (Lead ML Engineer at Grammarly)
Experts:
- Chad Mills (Leads Grammarly's Applied Research)
- Thomas Wolf (Co-founder and CEO at Hugging Face Inc.)
- Vitaliy Radchenko (Data Scientist at YouScan)
More talks and videos from the conference:
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Fwdays has been organizing large-scale conferences for developers for more than 10 years for the following spheres: JavaScript, .NET, Python, Data Science, PHP, QA, Highload, Architecture, DevOps, Databases.
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