Machine learning works by using algorithms to parse data, learn from it, and then make determinations or predictions. Here’s a simplified explanation of the steps involved: ...

Like everything else associated with machine learning, deep learning, and large language models, the generative AI development process is subject to change, often with little or no notice.

Training a machine learning model might sound tricky at first, but it’s actually pretty doable when you break it into steps. Whether you’re working with customer info, photos, or trying ...

Data cleaning goes by many names—including data scrubbing, data purification, data refinement and data validation—all of which refer to the process of preparing data for analysis by ...

Of 71 papers related to medicine, 27 papers contained AI models with critical errors. Some research shows that the tradeoff between fairness and efficacy in AI can be eliminated with intentional ...

The FDA defines process validation as consisting of three parts: process design (PD), process qualification (PQ), and continued process verification (CPV). The first two stages are discrete—once ...