AiDotNet

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AiDotNet

This is a library (currently in preview) for getting the latest and greatest ai algorithms and bringing them directly to the .net community. Our approach for this library was to both provide an easy way for beginners to be able to use AI/ML since it usually has a very steep learning curve, and an easy way for expert level users to be able to fully customize everything about our algorithms. For now we are showcasing our simplified approach by providing simple linear regression to get feedback on how we can improve our library. We will be adding more algorithms in the future and we are open to any contributions to this library. Please let us know what you think about our approach. We will be handling all ai algorithms using the same methods.

AiDotNet Examples

This repository contains examples of using the AiDotNet machine learning library for various tasks.

Table of Contents

  1. Introduction
  2. Getting Started
  3. Example Descriptions
  4. Running the Examples

Introduction

AiDotNet is a .NET machine learning library for building, training, and deploying machine learning models in C#. These examples demonstrate how to use its various features for different scenarios.

Getting Started

To run these examples, you need:

Clone this repository and open it in Visual Studio or your preferred IDE.

Example Descriptions

Basic Examples

  1. Neural Network Example - Demonstrates how to use neural networks for classification (Iris dataset) and regression (housing prices).
  2. Multiple Regression Example - Shows how to build a linear regression model to predict house prices.
  3. Time Series Example - Illustrates forecasting stock prices using time series models.

Advanced Real-World Examples

  1. Enhanced Regression Example - A comprehensive real estate analysis with feature engineering, model selection, and evaluation.
  2. Enhanced Neural Network Example - Customer churn prediction with data preprocessing, model training, and business insights.
  3. Enhanced Time Series Example - Energy demand forecasting with multiple models and seasonal analysis.

Running the Examples

Execute the project and choose an example from the menu. Each example demonstrates different aspects of machine learning with AiDotNet.

For more information about AiDotNet, visit [GitHub Repository Link].

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