Pitfalls (Avoid)
User Trust and EngagementExplainabilityAvoid notebooks in productionPoor security practicesDon’t treat accuracy as the only or even the best way to evaluate your algorithmUse machine learning judiciouslyDon’t forget to understand the at-inference usage profileDon’t make it difficult for a data scientists to access data or use the tools they needNot taking into consideration the downstream application of the model
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