README-0.1.md

ML.NET Samples

Overview

ML.NET is a cross-platform open-source machine learning framework that makes machine learning accessible to .NET developers.

The official ML.NET samples are divided in three categories:

• Getting started (C#) - basic "hello world" samples for each ML task, in C#
• Getting started (F#) - basic "hello world" samples for each ML task, in F#
• Examples - examples of how you can use various ML.NET components (learners/algorithms, transforms, etc. This is the area that will be growing significantly, covering many scenarios).
• End-to-end (C#) - real world examples of web, desktop, mobile, and other applications infused with ML solutions via ML.NET APIs.

For VB.NET samples, check this external repo supported by the community (Kudos for Nukepayload2): https://github.com/Nukepayload2/machinelearning-samples/tree/master/samples/visualbasic

Since the list of examples will be growing and they will be covering many scenarios depending on ML tasks but also showing typical business problems to solve, the samples are classified by two pivots:

• ML task/area
• Industry/business

Samples Gallery classified by ML task

Binary Classification	Customer reviews sentiment analysis Titanic Passenger Survival Prediction
Multi-class classification	GitHub issues labeler Iris classification
Regression	Taxi fare prediction Bike sharing demand Product sales forecast
Recommendation	eCommerce product catalog recommender Movies recommender
Clustering	Customer segmentation Clustering Iris Data
Anomaly detection	Fraud detection in credit cards
Ranking	TBD
Time Series Forecasting	TBD

Samples for predicting/scoring already trained models from other frameworks

Tensorflow model scoring	Classify/Identify images Image style transfer Use TensorFlow model as featurizer in ML.NET
ONNX model scoring	Sentiment analysis of faces in photos

The next gallery showcases the same examples but classified by industry/business

Samples Gallery classified by Industry/Business

Retail samples	eCommerce product catalog recommender Product sales forecast Movies recommender Customer reviews sentiment analysis
Transport & travel	Taxi Fare Prediction Bike Sharing Demand
Financial services samples	Fraud detection in credit cards
Marketing samples	Customer segmentation
Academic & research samples	Iris classification Clustering Iris Data Titanic Passenger Survival Prediction
Development & computing	GitHub issues labeler
Any industry/business	Classify/Identify images Sentiment analysis of faces in photos Use TensorFlow model as featurizer in ML.NET Image style transfer

NuGet packages to use

Until ML.NET is released as final v1.0, most of the samples in this repo will be using preview released versions (i.e. v0.6, v0.7, etc.) available at NuGet (using released Microsoft.ML NuGet packages). However, a few of the samples might also be using nightly releases available at MyGet using this feed: https://dotnet.myget.org/F/dotnet-core/api/v3/index.json.

In addition, if you would like to explore the examples directly referencing the source code of ML.NET, check out scenario tests in ML.NET repository.

Learn more

See ML.NET Guide for detailed information on tutorials, ML basics, etc.

API reference

Check out the ML.NET API Reference to see the breadth of APIs available.

Contributing

We welcome contributions! Please review our contribution guide.

Community

Please join our community on Gitter

This project has adopted the code of conduct defined by the Contributor Covenant to clarify expected behavior in our community. For more information, see the .NET Foundation Code of Conduct.

License

ML.NET Samples are licensed under the MIT license.