How Do I Use ONNX Runtime Web For AI In My JavaScript Project? - Learning To Code With AI

Описание: How Do I Use ONNX Runtime Web For AI In My JavaScript Project? Are you interested in adding AI capabilities directly into your web applications? In this video, we’ll guide you through the process of using ONNX Runtime Web for AI inference in JavaScript projects. You’ll learn how to incorporate this powerful library into your code, load pre-trained models, and run predictions efficiently right in the browser. We’ll cover how to prepare your data as tensors, handle model outputs, and optimize performance with WebAssembly and WebGL backends. This approach allows you to create smarter, more interactive web apps without relying on servers, ensuring data privacy and reducing server load. Whether you're working with images, text, or other data types, we’ll show you how to convert your inputs into the right format for your models and interpret the results effectively. Plus, we’ll discuss how to integrate AI features seamlessly into any JavaScript framework or plain HTML setup, making it easy to trigger predictions with user interactions. For larger projects, we’ll share tips on bundling and optimizing your code for faster load times. If you want to bring AI into your web pages in a simple, efficient way, this video is perfect for you. Join us to learn how to enhance your projects with client-side AI inference using ONNX Runtime Web.

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