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02:45 Luigi Patruno
04:50 How can ML teams be more rigorous in their engineering practices?
10:25 Best practices for monitoring and logging ML systems
18:00 Adding business value with data science
37:10 Most valuable types of tools for ML in production
43:15 What an ideal data pipeline setup looks like
47:50 Unbundling the "Data Scientist" role
50:35 The future of building software: "Code 2.0"
59:45 Most valuable skills for the future
01:10:15 Learnings from writing his blog "ML in Production"
01:15:00 Rapid fire questions