Learn ONNX with Real Code Examples

Understand ML model training in PyTorch or TensorFlow

Learn ONNX model export and import

Practice inference using ONNX Runtime

Experiment with model optimization and quantization

Deploy ONNX models on edge and cloud platforms

Week 1: Export simple models to ONNX

Week 2: Validate ONNX model inference matches original framework

Week 3: Apply optimizations and quantization

Week 4: Deploy models on GPU/CPU backends

Week 5: Integrate ONNX models into production pipelines

What is ONNX and why is it used?

How do you export a PyTorch model to ONNX?

Explain ONNX Runtime and its advantages

How do you optimize an ONNX model for inference?

What are limitations of ONNX for deployment?

ModelProto = serialized ONNX model

Graph = computation graph of nodes

Node = operator in the graph

Tensor = multi-dimensional data array

ONNX Runtime = inference engine

Practical ONNX

Deploying AI Models with ONNX Runtime

Cross-Framework Machine Learning with ONNX

ONNX for Edge and Cloud AI

Optimizing Inference with ONNX

ONNX official tutorials

ONNX Runtime performance examples

PyTorch to ONNX export notebooks

TensorFlow to ONNX conversion guides

Hands-on optimization and quantization exercises

https://onnx.ai/

https://github.com/onnx/onnx

https://onnxruntime.ai/

ONNX GitHub repository

ONNX Runtime GitHub

StackOverflow ONNX tag

ONNX Slack/Discord

Microsoft AI developer forums

ONNX GitHub repository

ONNX Runtime GitHub repository

StackOverflow ONNX tag

ONNX Slack and forums

Microsoft and Facebook ML developer communities