EasyML 1.0.0-beta2

.NET Standard 2.1
This is a prerelease version of EasyML.
There is a newer version of this package available.
See the version list below for details.
NuGet\Install-Package EasyML -Version 1.0.0-beta2
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
dotnet add package EasyML --version 1.0.0-beta2
<PackageReference Include="EasyML" Version="1.0.0-beta2" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add EasyML --version 1.0.0-beta2
#r "nuget: EasyML, 1.0.0-beta2"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. Copy this into the interactive tool or source code of the script to reference the package.
// Install EasyML as a Cake Addin
#addin nuget:?package=EasyML&version=1.0.0-beta2&prerelease

// Install EasyML as a Cake Tool
#tool nuget:?package=EasyML&version=1.0.0-beta2&prerelease

EasyML

EasyML is a component to train a machine learning system and use it to get predictions with just a few lines of code. The objective of this project is to facilitate the use of ML algorithms in any project by any developer with no knowledge about ML. It is basically a wrapper to allow devs to focus only in get advantage from this technology as fast as possible instead of getting lost themselves in the implementation details.

Features

  • Regression implementation: A supervised machine learning implementation that is used to predict the value of a column (label) from a set of related features. The label can be of any real value.

How to use

1️⃣

Model your data

The first thing you must define is the data you will use to train your system and what are que predictions you want to get.

Suppose we need a ML system to predict the estimated time a expensive operation lasts. I can get the following data every time I performed one of those operations (that are the parameters/features of your system): Number of calls needed, Server we call, Total amount of data sent, weekday, daytime, Total seconds . I write this in a class:

class OperationSummary
{
	public int Calls { get; set; }
	public string DestinationIP { get; set; }
	public int AmountOfData { get; set; }
	public int Weekday { get; set; }
	public TimeOnly Daytime { get; set; }
	public uint TotalSeconds { get; set; }
}

⚠️WORK IN PROGRESS...

About performance

  • ML systems can consume a lot of time being trained (depending on how precise you want to be and how long you let it be trained). This operation can be done in parallel...

Roadmap

  • Save and load datasets from files
  • Save and load trained model to/from files
  • Other implementations like multiclass classification, clustering, anomaly detection, etc..

Credits and more information

This project uses Microsoft's Microsoft.ML.AutoML package, an implementation to create, train, evaluate and get predictions from ML models.

Product Versions
.NET net5.0 net5.0-windows net6.0 net6.0-android net6.0-ios net6.0-maccatalyst net6.0-macos net6.0-tvos net6.0-windows
.NET Core netcoreapp3.0 netcoreapp3.1
.NET Standard netstandard2.1
MonoAndroid monoandroid
MonoMac monomac
MonoTouch monotouch
Tizen tizen60
Xamarin.iOS xamarinios
Xamarin.Mac xamarinmac
Xamarin.TVOS xamarintvos
Xamarin.WatchOS xamarinwatchos
Compatible target framework(s)
Additional computed target framework(s)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
1.0.3 89 6/5/2022
1.0.2 178 2/11/2022
1.0.1 100 2/11/2022
1.0.0 117 2/11/2022
1.0.0-beta2 93 2/10/2022
1.0.0-beta1 78 2/10/2022

v.1.0.0-beta2
- Regression system