Description
Deploying AI models for real-time inference requires a careful balance between simplicity, performance, and reliability. Flask, with its lightweight and flexible nature, provides an excellent platform for serving AI models through RESTful APIs, making it an ideal choice for both prototype and production deployments.
Here is an approach to deploying AI models using Flask, covering everything from basic setup to production-grade implementations. Here’s how to create efficient APIs, handle concurrent requests, manage model loading, and ensure robust error handling while maintaining high performance for real-time inference.
Kognition.Info paid subscribers can download this and many other How-To guides. For a list of all the How-To guides, please visit https://www.kognition.info/product-category/how-to-guides/