---
title: API Basics
grand_parent: Tutorials
parent: Inferencing
nav_order: 1
---
# ONNX Runtime Inferencing: API Basics
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These tutorials demonstrate basic inferencing with ONNX Runtime with each language API. 


## Contents
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## Python
* [Scikit-learn Logistic Regression](https://microsoft.github.io/onnxruntime/python/tutorial.html)
* [Image recognition (Resnet50)](https://github.com/onnx/onnx-docker/blob/master/onnx-ecosystem/inference_demos/resnet50_modelzoo_onnxruntime_inference.ipynb)


## C++
* [Number recognition (MNIST)](../tutorials/mnist_cpp.html)
* [Image classification (Squeezenet)](https://github.com/microsoft/onnxruntime/blob/master/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests.Capi/CXX_Api_Sample.cpp)

## C
* [Image classification (Squeezenet)](https://github.com/microsoft/onnxruntime/blob/master/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests.Capi/C_Api_Sample.cpp)

## C#
* [Object detection (Faster RCNN)](../tutorials/fasterrcnn_csharp.html)
* [Image recognition (ResNet50 v2)](../tutorials/resnet50_csharp.html)

## Java
* [Number recognition (MNIST)](../tutorials/mnist_java.html)

## Node.js
* [Basic usage](https://github.com/microsoft/onnxruntime/tree/master/samples/nodejs)