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LEARN, CONNECT, BUILD

Microsoft Reactor

Neem deel aan Microsoft Reactor en neem live contact op met ontwikkelaars

Klaar om aan de slag te gaan met AI en de nieuwste technologieën? Microsoft Reactor biedt evenementen, training en communitybronnen om ontwikkelaars, ondernemers en startups te helpen bouwen op AI-technologie en meer. Kom kijken.

Terug

Mastering Semantic Classification with Embeddings and Vector Similarity in .NET/C#

3 april, 2025 | 3:00 p.m. - 3:45 p.m. (UTC) Coordinated Universal Time

  • Notatie:
  • alt##LivestreamLivestream

Onderwerp: Agents

Taal: Engels

GenAI Agents often hallucinate, generating misleading responses when they lack accurate grounding. The solution? Embedding-Based Classification with Vector Similarity - ensuring agents first classify queries correctly before retrieving trusted data.

Join this live session to learn how embedding models like Text-Embedding-Ada-002 leverage Semantic Similarity and Cosine Similarity to improve AI precision, reduce errors, and scale effortlessly in .NET/C# applications.

Why This Matters

  • Without proper classification, GenAI Agents can hallucinate, pulling in irrelevant or incorrect data and making unreliable predictions.
  • Vector-Based Embeddings solve this by capturing the Semantic Meaning of queries and mapping them to the right categories.
  • Ensures agents retrieve accurate, contextually relevant information based on Cosine Similarity, rather than generating misleading responses.

What You'll Learn

  • How Embeddings and Cosine Similarity prevent AI Hallucination, improve classification, and ensure accurate, contextually relevant responses.
  • Why pre-trained models like Text-Embedding-Ada-002 outperform custom models, and how to deploy them in Azure AI Foundry with hands-on coding in .NET/C#.
  • Best practices for managing Embedding Vectors and Semantic Similarity in GenAI-Driven Applications for scalability and precision.

Who Should Attend

  • .NET/C# Developers building AI-powered apps and solutions.
  • Engineers working on LLM/GenAI-based Agents, AI search, or automation.
  • Architects designing scalable AI solutions using Semantic and Vector-Based Models, and professionals aiming to enhance AI precision and scalability

Don't miss this chance to level up your AI Skills and make your agents smarter, faster, and more reliable using Vector Embeddings and Semantic Similarity!

#GenerativeAI #AIEmbedding #AzureAI #DotNetAI #SemanticSearch

Sprekers

  • Adit Sheth

    • Senior Software Engineer

    Microsoft

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