AlbiruniML is a linear algebra and machine learning library written in pure C# language inspired by tensorflow

Dive into the world of machine learning and explore how it empowers businesses to extract valuable insights from vast amounts of data. Discover practical techniques and tools for successful implementation.

In this article, we build a Retrieval-Augmented Generation (RAG) pipeline using KitOps, integrating tools like ChromaDB for embeddings, Llama 3 for language models, and SentenceTransformer for embedding models.

How to implement logistic regression in ML.NET?

In topic 2 of our series, we explore the power of multi-model databases for Intelligent Apps and their integration with Azure Cosmos DB and Azure Kubernetes Service (AKS).

In this four-part series, you’ll learn how to create an Intelligent App with Azure. This first tutorial walks you through what Azure AI and Azure Container Apps are, how to set up an Azure environment, and building your basic application.

Learn to create real-time computer vision applications with a couple of Python functions and a model URI.

In this four-part series, you’ll learn how to create an Intelligent App with Azure. This second tutorial demonstrates how to add intelligent features to this user feedback analysis application. Then, it explores how to use your new Intelligent App to analyze user feedback.

In this article we will explore how self-hosted AI, specifically CodeProject.AI Server, empowers businesses to leverage the power of AI while maintaining control over their data.

This article will show you how to create a module for CodeProject.AI Server that wraps some code that takes a long time to complete