ML.NET MLFlow Sample Application
This application demos how to track model runs in MLFLow for models built using Automated ML in ML.NET. For more details check out the accompanying blog post.
This project was built on an Ubuntu 18.04 PC but should work on Windows and Mac. Note that MLFlow does not natively run on Windows at the time of this writing. To run it on Windows use Windows Subsystem for Linux (WSL).
Get The Data
The data used in this dataset comes from the UCI Machine Learning Repository and looks like the data below:
5.1,3.5,1.4,0.2,Iris-setosa 4.9,3.0,1.4,0.2,Iris-setosa 4.7,3.2,1.3,0.2,Iris-setosa 4.6,3.1,1.5,0.2,Iris-setosa
First, create a directory for the data inside the console application directory:
Then, download and save the file into the
curl -o Data/iris.data https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data
Run The Application
Start MLFlow Server
In the terminal, from the console application directory, enter the following command to start the MLFlow Server:
http://localhost:5000 in your browser. This will load the MLFLow UI.
Then, in another terminal, from the console application directory, enter the following command to run the experiment:
dotnet build dotnet run