Combining Statistics and Expert Human Judgment for Better Recommendations

Combining Statistics and Expert Human Judgment for Better Recommendations: Most algorithmic recommendation engines target the consumer directly. Combining these recommendation algorithms with expert human selection and curation can make them more effective. But it also makes things more complicated. In this talk I’ll share lessons from combining statistics and human judgement for personal styling recommendations at Stitch Fix, where we are committed to our recommendations through the physical delivery of merchandise to clients. I’ll discuss both statistical and practical challenges of machine learning with humans in the loop: training with selection bias, making predictions for human consumption and measuring success.

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