Semantic kernel is a mathematical representation of text data that captures the underlying semantics, concepts, and relationships between words and documents in a high-dimensional vector space. It is used in natural language processing (NLP) and information retrieval tasks, such as document classification, clustering, and similarity analysis, for capturing semantic meaning and context in text data. Readers can explore semantic kernel algorithms, embeddings, and applications for analyzing and understanding text data, enabling advanced NLP tasks and applications.

Semantic Kernel

Using Semantic Kernel to create a Time Plugin with .NET

How to Get Started using Semantic Kernel .NET

Large Language Models, Open API, View Models and the Backend for Frontend Pattern

Generating API Manifests for Semantic Kernel

Microsoft Build – Community Testimonial Videos

Filters in Semantic Kernel

Introducing API Manifest Plugins for Semantic Kernel

Unit Testing with Semantic Kernel

Making Plans with Semantic Kernel: Implementing the Microsoft Graph Plugin

Unlock AI Collaboration at Microsoft BUILD 2024 with Semantic Kernel