# Next Steps

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/)
- [Understand ONNX fundamentals and architecture](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/01_fundamentals/)
- [Set up your development environment](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/02_setup/)
- [Generate a synthetic Sudoku digit dataset](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/03_preparingdata/)
- [Train the digit recognizer](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/04_training/)
- [Run inference and evaluate the model](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/05_inference/)
- [Build the Sudoku processor pipeline](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/06_sudokuprocessor/)
- [Optimize the model for Arm64 deployment](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/07_optimisation/)
- [Deploy the model to Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/08_android/)
- [Next Steps](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/_next-steps/)

## Deployment Overview

Deploy optimized ML models with ONNX Runtime on Arm platforms.

## Next Steps
- [Introduction](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/)
- [Understand ONNX fundamentals and architecture](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/01_fundamentals/)
- [Set up your development environment](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/02_setup/)
- [Generate a synthetic Sudoku digit dataset](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/03_preparingdata/)
- [Train the digit recognizer](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/04_training/)
- [Run inference and evaluate the model](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/05_inference/)
- [Build the Sudoku processor pipeline](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/06_sudokuprocessor/)
- [Optimize the model for Arm64 deployment](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/07_optimisation/)
- [Deploy the model to Android](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/08_android/)
- [Next Steps](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/onnx/_next-steps/)

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- Have more feedback? [Log an issue on GitHub.](https://github.com/ArmDeveloperEcosystem/arm-learning-paths/issues/new?title=Feedback%20-%20Deploy%20optimized%20ML%20models%20with%20ONNX%20Runtime%20on%20Arm%20platforms)
- Want to collaborate? [Join our Discord server.](https://discord.com/invite/armsoftwaredev)

## Continue Learning

### Read related resources

Find more information about the topics in this Learning Path:
- [ONNX](https://onnx.ai)
- [ONNX Runtime](https://onnxruntime.ai)
- [Getting Started with ONNX Runtime on Mobile](https://onnxruntime.ai/docs/tutorials/mobile)
- [Optimizing Models with ONNX Runtime](https://onnxruntime.ai/docs/performance/model-optimizations.html)

### Join the Arm Developer Program

Connect, upskill, and build with the Arm Developer Community. Join today for hands-on technical resources and education materials, along with the support of Arm engineers and the broader ecosystem.

### Back to all learning paths under Mobile, Graphics, and Gaming

[Back](https://learn.arm.com/learning-paths/mobile-graphics-and-gaming/)