ONNX Explained: The Ultimate Guide to Universal Model Deployment & MLOps

Are your incredible ML models stuck in one framework, slow to deploy, and impossible to scale? While you're wrestling with compatibility issues, top engineers are shipping models that run anywhere at peak performance. Don't get left behind in the old way of doing MLOps! This video is your one-stop guide to mastering the ONNX ecosystem—the secret to universal, high-speed model deployment. Watch now or watch your projects fall behind.

Unlock the power of efficient MLOps with the Open Neural Network Exchange (ONNX). This video provides a complete walkthrough of the ONNX ecosystem, designed to free your AI models from framework lock-in and enable universal deployment.

What you will master in this guide:

ONNX Fundamentals: Learn how ONNX acts as a universal standard for ML models and explore its core architecture, including operators and opset versioning.
Essential Tooling: Visualize your models with tools like Netron.
High-Performance Inference: Dive deep into ONNX Runtime (ORT), the high-performance engine, and learn to use Execution Providers (EPs) for massive hardware acceleration.
Model Conversion & Optimization: Get practical, step-by-step workflows for converting your PyTorch and TensorFlow models to ONNX and optimizing them with techniques like quantization.
End-to-End Project: See it all come together in a capstone project where we deploy an optimized object detection model to the cloud, edge devices, and in the browser!
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Видео ONNX Explained: The Ultimate Guide to Universal Model Deployment & MLOps канала HustlerCoder