CNTK/Examples/TrainingCSharp

CNTK C#/.NET API training examples

Overview

This folder contains examples using CNTK C# API to build, train, and evaluate CNTK neural network models.

Getting the Data and Model

Data and model preparation are done with python scripts.

To install CIFAR10 dataset, change directory to Examples\Image\DataSets\CIFAR-10, run:

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python install_cifar10.py 

To install VGG flower and animal data and to download the ResNet model, change directory to Examples\Image\TransferLearning, run:

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python install_data_and_model.py

Build and Run Examples

1. Install Nuget package CNTK.CPUOnly version v2.2.0 or higher for CSTrainingCPUOnlyExamples.
2. Install Nuget package CNTK.GPU version v2.2.0 or higher for CSTrainingGPUExamples
3. Run following examples:

LogisticRegression

A hello-world example to train and evaluate a logistic regression model using C#/API. See CNTK 101: Logistic Regression and ML Primer for more details.

MNISTClassifier

This class shows how to build and train a classifier for handwriting data (MNIST).

CifarResNetClassifier

This class shows how to do image classification using ResNet. The model being built is a lite version of Deep Residual Learning for Image Recognition. See Python Tutorials for more details.

TransferLearning

This class demonstrates transfer learning using a pretrained ResNet model. See Python Tutorials for more details.

LSTMSequenceClassifier

This class shows how to build a recurrent neural network model from ground up and how to train the model.