ML.NET Cat vs Dog

ML.NET Model Builder is an intuitive graphical Visual Studio extension to build, train, and deploy custom machine learning models.
Model Builder uses automated machine learning (AutoML) to explore different machine learning algorithms and settings to help you find the one that best suits your scenario.

-Select Image Classification Scenario

-Select Trainning Environment

-Once you have chosen your scenario, Model Builder asks you to provide a dataset

-Train

-In my case, this training lasted a little over 4 hours

-Evaluate

-Consume

-Add solution ConsoleApp and WebApi

OPEN PowerShell and Test your WebAPI
$body = @{ImageSource = "Image location on your local machine"
Invoke-RestMethod "https://localhost:'PORT'/predict" -Method Post -Body ($body | ConvertTo-Json) -ContentType "application/json"

And that's it, in simple steps we create and consume a Machine Learning model. In the Documentation links you will see how to install the Model Builder extension in Visual Studio and everything related to ML.NET.

Happy coding!

Pablo Piovano.

DataSet: https://www.kaggle.com/muhammadshahzadkhan/dogvscat

ML.NET Documentation

• https://docs.microsoft.com/en-us/dotnet/machine-learning/

• https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotnet/model-builder

GitHub: https://lnkd.in/duBTphVJ