As industries embrace Artificial intelligence (AI) in key decision-making processes, it’s important to ensure that the accuracy of these AI solutions in production is sustained. While measuring accuracy offline with testing datasets is relatively straightforward, doing so in a production environment presents unique challenges. In this article, we will explore the need for measuring accuracy in production, challenges associated with the same and best practices to address those challenges using examples.
Need for measuring accuracy in productionMeasuring the accuracy of AI solutions in production is crucial as accurate AI solutions have a direct impact on business outcomes and ROI. AI-infused products can deliver the best user experience as we see in retail and e-commerce. However, an i
Council Post: Measuring Accuracy Of AI Solutions In Production
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Measuring the accuracy of AI solutions in production is paramount, however, it comes with unique challenges due to the real-world complexities.
