Tech Events & Workshops
Discover and join virtual tech events, workshops, and meetups from the Ubuntu community worldwide. Connect with developers, engineers, and tech enthusiasts.
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Building Document Question-Answering Systems with Rust
A practical two-hour session on the principles behind document question-answering systems, with Rust as the implementation context. The session focuses on how applications can answer questions from a known set of documents instead of relying only on what a language model already knows. We will cover the core workflow: loading documents, preparing them for search, finding relevant passages, passing useful context to a model, and producing answers that stay connected to the source material. The goal is to teach the engineering ideas behind RAG systems without turning the session into a product demo or an abstract AI lecture. The emphasis is on system boundaries, retrieval quality, answer grounding, error handling, and the practical decisions developers need to make when building document-aware applications. Audience: entry-level and intermediate developers who want a practical session on document search, retrieval, grounded generation, and Rust application design. Outcomes: * Understand how document-based question answering systems work * Explain the purpose of chunking, embeddings, retrieval, and context assembly * Design a simple retrieve-first, answer-second workflow * Use Rust to organize the main parts of a small RAG application * Recognize common causes of poor or unsupported answers * Apply basic techniques for improving retrieval and answer quality * Think about how to evaluate whether the system is actually useful Format: two hours with a short framing walkthrough, a concrete example, discussion of tradeoffs, and a closing checklist for practice.
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Building Document Question-Answering Systems with Rust
A practical two-hour session on the principles behind document question-answering systems, with Rust as the implementation context. The session focuses on how applications can answer questions from a known set of documents instead of relying only on what a language model already knows. We will cover the core workflow: loading documents, preparing them for search, finding relevant passages, passing useful context to a model, and producing answers that stay connected to the source material. The goal is to teach the engineering ideas behind RAG systems without turning the session into a product demo or an abstract AI lecture. The emphasis is on system boundaries, retrieval quality, answer grounding, error handling, and the practical decisions developers need to make when building document-aware applications. Audience: entry-level and intermediate developers who want a practical session on document search, retrieval, grounded generation, and Rust application design. Outcomes: * Understand how document-based question answering systems work * Explain the purpose of chunking, embeddings, retrieval, and context assembly * Design a simple retrieve-first, answer-second workflow * Use Rust to organize the main parts of a small RAG application * Recognize common causes of poor or unsupported answers * Apply basic techniques for improving retrieval and answer quality * Think about how to evaluate whether the system is actually useful Format: two hours with a short framing walkthrough, a concrete example, discussion of tradeoffs, and a closing checklist for practice.
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De consommateur à créateur : prenez une longueur d’avance avec l’Intelligence Artificielle !
What if AI became your best tool for professional growth, creating faster, and seizing new opportunities? Join this exceptional free webinar organized by FasoCode-X and discover how to transform the way you work through artificial intelligence, data, and the cloud. Whether you are a student, entrepreneur, professional, or digital enthusiast, this event is a unique opportunity to understand the challenges and opportunities of AI in today's world.
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The Polylith Mindset: Build Faster Across Multiple Projects

The Polylith Mindset: Build Faster Across Multiple Projects

Building a voice agent for your business

Building a voice agent for your business

Save Tokens and Build with Data-Driven Clarity using Clojure(Script) -- Part 2

Save Tokens and Build with Data-Driven Clarity using Clojure(Script) -- Part 2

Save Tokens and Build with Data-Driven Clarity using Clojure(Script)

Save Tokens and Build with Data-Driven Clarity using Clojure(Script)
