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Reinforcement learning common use cases, recommendation engine, productivity - Susan Shu Chang the data scientist show#039
The Data Scientist Show
Is the New Recommendation Better?
When it comes to putting mottoes in a production, what are some common mistakes you see people make? Oh, that's aa good question, i think. Like smaller orgs, the data scientist is more likely to be the only data scientist. I might jot something down a jupitor notebook, and then after a little bit, i might export et and then put production. But it really depends on what the production is in that company. Some companies, theyretonizing the jupiter notebooks rit they just have to run the notebook, and the notebook like, write something to a data base. And they d like the data scientists can just hand this off,
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