The Future of .NET Core, Machine Learning, and AI

The integration of Machine Learning and Artificial Intelligence into the .NET Core ecosystem represents a significant advancement in software development capabilities. This comprehensive article examines the evolution of AI integration within .NET, highlighting key developments across multiple domains including ML.NET enhancements, generative AI capabilities, and the introduction of Microsoft.Extensions.AI. The article explores how these advancements have transformed developer workflows, improved performance metrics, and expanded the possibilities for AI-driven applications. Through a detailed examination of implementation patterns, performance improvements, and community engagement, this article demonstrates how the .NET ecosystem has emerged as a robust platform for AI development, supported by Microsoft's comprehensive educational resources and strong community infrastructure.

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Publication Details

Journal
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Published
2024-12-15
DOI
https://doi.org/10.32628/cseit2410612391
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

The Future of .NET Core, Machine Learning, and AI

Jagdip Keshavlal Jadav
International Journal of Scientific Research in Computer Science Engineering and Information Technology
Big Data and Business Intelligence
article

The Future of .NET Core, Machine Learning, and AI

Jagdip Keshavlal Jadav
article en

Abstract

The integration of Machine Learning and Artificial Intelligence into the .NET Core ecosystem represents a significant advancement in software development capabilities. This comprehensive article examines the evolution of AI integration within .NET, highlighting key developments across multiple domains including ML.NET enhancements, generative AI capabilities, and the introduction of Microsoft.Extensions.AI. The article explores how these advancements have transformed developer workflows, improved performance metrics, and expanded the possibilities for AI-driven applications. Through a detailed examination of implementation patterns, performance improvements, and community engagement, this article demonstrates how the .NET ecosystem has emerged as a robust platform for AI development, supported by Microsoft's comprehensive educational resources and strong community infrastructure.

International Journal of Scientific Research in Computer Science Engineering and Information TechnologyVol. 10(6)
Cognia (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 63%
Big Data and Business Intelligence
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The Future of .NET Core, Machine Learning, and AI — Jagdip Keshavlal Jadav · International Journal of Scientific Research in Computer Science Engineering and Information Technology (2024) | TGRS Research Map | TGRS