Evaluating Deep Learning Models in 10 Different Languages (With Examples)
Tags: machinelearning, azure, onnx, deeplearning
Published: 2020-05-05 13:42:18

---
title: Evaluating Deep Learning Models in 10 Different Languages (With Examples)
published: true
date: 2020-05-055 13:25:26 UTC
tags: machinelearning,azure,onnx,deeplearning
canonical_url: https://medium.com/microsoftazure/evaluating-deep-learning-models-in-10-different-languages-with-examples-a84d4c5d4beb
---

![](https://cdn-images-1.medium.com/max/1024/0*LJem382v2F1hUFZL.png)

**ONNX is an open format built to represent machine learning models.** ONNX defines a common set of operators — the building blocks of machine learning and deep learning models — and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers. The following post is a compilation of code samples showing how to evaluate Onnx Models in 10 different programming languages.

#### #10 R

![](https://cdn-images-1.medium.com/max/724/0*BqjJTjVfSfQjCNUb.png)

[onnx/onnx-r](https://github.com/onnx/onnx-r)

#### #9 C++

![](https://cdn-images-1.medium.com/max/505/1*ABuEflLQ3cVOtfT5y1tKIA.png)

[microsoft/onnxruntime](https://github.com/microsoft/onnxruntime/blob/master/samples#CC)

#### #8 Java

![](https://cdn-images-1.medium.com/max/167/0*7Nwv1EgLTtx46Iba)

[microsoft/onnxruntime](https://github.com/microsoft/onnxruntime/blob/master/docs/Java_API.md)

#### #7 .NET Core

![](https://cdn-images-1.medium.com/max/400/0*AQOfL4rMx9rpnl3l)

[Tutorial: Detect objects using an ONNX deep learning model - ML.NET](https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/object-detection-onnx)

#### #6 Ruby

![](https://cdn-images-1.medium.com/max/241/0*KAyQ5z8U0txvGESJ)

[ankane/onnxruntime](https://github.com/ankane/onnxruntime)

#### #5 Rust

![](https://cdn-images-1.medium.com/max/1024/0*ct5qgjAi1z2S0imH.jpg)

[microsoft/onnxruntime-tvm](https://github.com/microsoft/onnxruntime-tvm/tree/master/rust)

#### #4 JavaScript

![](https://cdn-images-1.medium.com/max/264/0*okSXgcamskyXq4F2.png)

[microsoft/onnxjs](https://github.com/microsoft/onnxjs)

#### #3 Python

![](https://cdn-images-1.medium.com/max/512/0*9CkgIRmwjxDfgbAG.png)

[onnx/onnx](https://github.com/onnx/onnx/blob/master/docs/PythonAPIOverview.md)

#### #2 Swift

![](https://cdn-images-1.medium.com/max/1024/0*BpePt0HX2DUWAXkT.png)

[Convert fast.ai trained image classification model to iOS app via ONNX and Apple Core ML](https://link.medium.com/uJVunyb4d4)

#### #1 C

![](https://cdn-images-1.medium.com/max/349/1*sIVMLcNeyfxZixZOJ17NWg.png)

[microsoft/onnxruntime](https://github.com/microsoft/onnxruntime/blob/master/docs/C_API.md)

### Next Steps

- [Tutorial: Detect objects using an ONNX deep learning model - ML.NET](https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/object-detection-onnx?WT.mc.id=aiapril-medium-abornst)
- [microsoft/OLive](https://github.com/microsoft/OLive)

### About the Author

[**Aaron (Ari) Bornstein**](https://www.linkedin.com/in/aaron-ari-bornstein-22aa7a77/) is an AI researcher with a passion for history, engaging with new technologies and computational medicine. As an Open Source Engineer at Microsoft’s Cloud Developer Advocacy team, he collaborates with Israeli Hi-Tech Community, to solve real world problems with game changing technologies that are then documented, open sourced, and shared with the rest of the world.

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