Best Practices for Creating Domain-Specific AI Models - KDnuggets

Large-scale general AI implementations serve as great building blocks for solving certain B2B problems, and most organizations have already or are in the process of leveraging them. However, the desire for immediate RoI, creating fail-fast prototypes, and delivering decision-centric outcomes are driving the need for domain-specific AI initiatives. Use cases and subject matter expertise help, but data scientists and analysts need to adapt the AI implementation cycle to resolve problems that require more specificity and relevancy. The biggest hurdle anyone would encounter while building such AI models is finding quality, domain-specific data. Here are some best practices and techniques for domain-specific model adaptation that worked for us time and again.