Join 📚 Kevin's Highlights
A batch of the best highlights from what Kevin's read, .
**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
The core Azure technologies used to implement data engineering workloads include:
• Azure Synapse Analytics
• Azure Data Lake Storage Gen2
• Azure Stream Analytics
• Azure Data Factory
• Azure Databricks
Data engineering in Microsoft Azure - Training
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Microsoft Azure includes many services that can be used to implement and manage data engineering workloads.
Data engineering in Microsoft Azure - Training
wwlpublish
...catch up on these, and many more highlights
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