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.NET Conf: Focus on AI is a free, one-day livestream event that features speakers from the community and Microsoft teams working on integrating AI into .NET applications. Learn how to build intelligent applications with .NET using the latest AI libraries and tools, enhance existing applications with AI features, and see real-world examples of AI in action. Tune into focus.dotnetconf.net on August 20, 2024. Ask questions live and learn how to make your .NET applications smarter.

| Session | Speaker | | :------------------------- |:------------------------- | | Keynote - State of .NET + AI | Scott Hanselman, Maria Naggaga and guests | | Get started incorporating AI into your .NET applications and services | Stephen Toub | | Better together: .NET Aspire and Semantic Kernel | Steve Sanderson and Matthew Bolanos | | Build interactive AI-powered web apps with Blazor and .NET | Daniel Roth | | Navigating the world of AI models in .NET: From local development to the cloud | Bruno Capuano | | OpenAI and Azure OpenAI: A .NET SDK convergence story | Matt Soucoup and Roger Pincombe | | Agents: Patterns and practices for automating business workflows | Kosta Petan and XiaoYun Zhang | | RAG on your data with .NET, AI and Azure SQL | Davide Mauri | | Building Generative AI apps with your data in Azure Cosmos DB | James Codella | | Integrating Semantic Search Capabilities with .NET and Azure: Milvus Vector Database | Tim Spann | | H&R Block: Lessons learnt from applying Generative AI to apps with .NET and Azure | Vin Kamat | | Add Generative AI capabilities to your .NET Web app for Azure App Service | Gaurav Seth | | Observing AI applications from dev to production with .NET Aspire | Anthony Shaw | | Infuse AI in your Windows apps with Windows Copilot Runtime and .NET | Nikola Metulev | | Build your own copilot with Teams AI library and .NET | Ayca Bas and John Miller | | RAG with AI Search and .NET | Matt Gotteiner |

Dive into the world of SQL on Hadoop and get the most out of your Hive data warehouses. This book is your go-to resource for using Hive: authors Scott Shaw, Ankur Gupta, David Kjerrumgaard, and Andreas Francois Vermeulen take you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stored across your Hadoop environment. From deploying Hive on your hardware or virtual machine and setting up its initial configuration to learning how Hive interacts with Hadoop, MapReduce, Tez and other big data technologies, Practical Hive gives you a detailed treatment of the software. In addition, this book discusses the value of open source software, Hive performance tuning, and how to leverage semi-structured and unstructured data. What You Will Learn Install and configure Hive for new and existing datasets Perform DDL operations Execute efficient DML operations Use tables, partitions, buckets, and user-defined functions Discover performance tuning tips and Hive best practices Who This Book Is For Developers, companies, and professionals who deal with large amounts of data and could use software that can efficiently manage large volumes of input. It is assumed that readers have the ability to work with SQL.