AiDotNet

The comprehensive .NET machine learning library

AiDotNet provides everything you need to build, train, and deploy machine learning models in .NET applications.

Section	Description
Getting Started	Installation and first steps
Tutorials	Step-by-step learning guides
API Reference	Complete API documentation
Examples	Code examples and samples

Features

Neural Networks: Dense, CNN, RNN, LSTM, Transformer architectures
Classical ML: Classification, Regression, Clustering, Dimensionality Reduction
Computer Vision: Image classification, object detection, segmentation
NLP: Text classification, embeddings, RAG pipelines
Audio: Speech recognition (Whisper), TTS, speaker diarization
Time Series: Forecasting, anomaly detection
GPU Acceleration: CUDA, OpenCL, Metal support
Cross-Platform: Windows, Linux, macOS

Installation

dotnet add package AiDotNet

Quick Example

using AiDotNet;
using AiDotNet.Classification;

// Train a classifier
var result = await new AiModelBuilder<double, Matrix<double>, Vector<double>>()
    .ConfigureModel(new RandomForestClassifier<double>(nEstimators: 100))
    .ConfigurePreprocessing()
    .ConfigureCrossValidation(new KFoldCrossValidator<double>(k: 5))
    .ConfigureDataLoader(new InMemoryDataLoader<double, Matrix<double>, Vector<double>>(features, labels))
    .BuildAsync();

// Make predictions
var prediction = result.Predict(newSample);

Try It Online

Check out the Interactive Playground to experiment with AiDotNet directly in your browser.