Join 📚 Kevin's Highlights
A batch of the best highlights from what Kevin's read, .
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From Day One to 100: The Seattle Data Guy Journey in One Special Issue
SeattleDataGuy
**Are you aware of the risks?**
You need to know about the reasonably foreseeable risks and impact of your AI product before putting it on the market.
If something goes wrong – maybe it fails or yields biased results – you can’t just blame a third-party developer of the technology.
And you can’t say you’re not responsible because that technology is a “black box” you can’t understand or didn’t know how to test.
Keep Your AI Claims in Check
Federal Trade Commission
Here’s what the entity resolution query looks like:
I’m joining the table with itself on state + zipcode
to reduce the search space and
using string similarity thresholds
for filtering potential duplicates.
In entity resolution methodology this is known as “blocking.”
Fundamental Data Engineering Concepts - Part 2
Ergest Xheblati
...catch up on these, and many more highlights
Readwise