Sentence Similarity Example using ML.NET

A C# implementation of sentence similarity analysis using ML.NET, leveraging Microsoft's ML.NET Model Builder for accurate text comparison.

🎯 Project Overview

This project implements sentence similarity comparison using ML.NET framework. It was developed to explore ML.NET's natural language processing capabilities, specifically focusing on measuring semantic similarity between text sentences.

🚀 Features

• Text similarity analysis using ML.NET
• Pre-trained model for immediate use
• Sample dataset with 500 sentence pairs
• Easy-to-use implementation
• Model Builder integration

📁 Repository Structure

SentenceSimilarityExample/

├── Source Files

│ ├── Program.cs # Main program entry point

│ ├── MLModel1.consumption.cs # Model consumption logic

│ ├── MLModel1.training.cs # Model training implementation

│ ├── MLModel1.mbconfig # Model Builder configuration

│ └── MLModel1.mlnet # Trained ML.NET model

├── Data

│ └── sentence_similarity_500.csv # Training dataset

└── Project Files

├── SentenceSimilarityExample.csproj

└── SentenceSimilarityExample.sln

🔧 Prerequisites

• Visual Studio 2022
• .NET 6.0 or later
• ML.NET Model Builder extension for Visual Studio

🏃‍♂️ Getting Started

1. Clone the Repository

   git clone https://github.com/iamrealvinnu/SentenceSimilarityExample.git

2. Open the Solution

   • Launch Visual Studio 2022
   • Open SentenceSimilarityExample.sln

3. Build and Run

   • Build the solution (Ctrl + Shift + B)
   • Run the project (F5)

💡 Usage Example

// Create ML model

MLModel1.ModelInput sampleData = new MLModel1.ModelInput()

{

Sentence1 = "First sentence to compare",

Sentence2 = "Second sentence to compare"

};

// Make prediction

var result = MLModel1.Predict(sampleData);

📚 References

• Sentence Similarity ML.NET Model Builder
• ML.NET Documentation

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions, issues, and feature requests are welcome! Feel free to check issues page.

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Developed using ML.NET