Constructive criticism: overcoming the four biggest challenges of feedback loops in machine learning

You should build feedback loops into your machine learning implementations, but how do you do it right?

Machine learning is becoming a key enabler of an increasingly diverse set of products and business workflows. Whether you’re a legal information service helping your users analyze court cases or you’re an e-commerce retailer recommending purchases to your customers, chances are that machine learning is (or will soon be) an integral part of your solution. But machine learning is not a one-time implementation — rather, you have to keep your models current and ­unbiased. That’s where the pitfalls abound.

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