Data Science #31

In this issue: 10 Python datetime pitfalls; data science with impact; on high-quality human data; quantifying reputation and success in art; AI for data journalism; what does a confidence interval mean?; an introduction to SQL for weary data scientists; and more.

The sponsor of this issue is Galileo .

• 10 Python datetime pitfalls, and what libraries are (not) doing about it
• Data science with Impact
• Thinking about high-quality human data
• [Sponsored] GenAI Productionize 2.0

"I'm blown away by the high quality and value of this event. " - Ricardo B., "Great event - worth getting up at 4am in the morning for! " - Sandy A., "What an amazing and insightful summit! " - Madhumita R. Don't miss GenAI Productionize 2.0 – the premier conference for GenAI application development!

• [Project] Quantifying reputation and success in art
• AI for data journalism: demonstrating what we can do with this stuff right now
• Forecast evaluation for data scientists: common pitfalls and best practices
• [Tutorial] What does a confidence interval mean ?
• An introduction to SQL for weary data scientists

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