API Endpoints
AI Infrastructure
The creation of interfaces that allow other systems to interact with deployed ML models.
Detailed Explanation
API Development in AI Infrastructure involves designing and building interfaces that enable seamless communication between software applications and deployed machine learning models. These APIs facilitate integration, allowing external systems to send data and receive predictions or insights efficiently, ensuring scalable and secure access to AI functionalities for various applications, from web services to enterprise solutions.
Use Cases
- •Integrate ML models into web apps for real-time predictions, enabling seamless data exchange between user interfaces and AI systems.
Related Terms
Other terms in the AI Infrastructure category