PyData Eindhoven 2024
Eindhoven, The Netherlands —
Retrieval Augmented Generation (RAG) is powerful. Let's go from Basic (chunking, vector embeddings, nearest-neighbor search) to Hybrid Search (TF-IDF, BM-25 and Reciprocal Rank Fusion) to Advanced (PDF parsing, tables, graphs) and finally, the cutting edge: Multimodal.
PyData London 2024
London, United Kingdom —
MLOps takes the best of DevOps and applies it to operationalizing ML, introducing concepts like experiment tracking, dataset versioning, model registries, ML pipelines, CI/CD and better observability. But MLOps goes beyond just tech- MLOps is also about People and Process.
AI Community Day 2024
Utrecht, The Netherlands —
LLMOps on Azure: scaling RAG applications, using Azure AI Search (keyword and vector search, reciprocal rank fusion), hosting LLM apps on Azure Container Apps, IaC with Terraform, robust CI/CD setups and an elaborate observability stack with Langfuse/OpenTelemetry.
RAG on GCP: production-ready GenAI on Google Cloud Platform (on Xebia.com ⧉)
GCP has an increasing set of managed services that can help you build production-ready Retrieval Augmented Generation (RAG) applications. How can you best leverage them to build RAG applications? Let’s explore together. Read along!
PyCon SK 2024
Bratislava, Slovakia —
What are the prerequisites you need before you can properly adopt MLOps? Let's learn together: why MLOps, what it is, how it relates to DevOps- and how you can best adopt it.
Dataset enrichment using LLM’s ✨ (on Xebia.com ⧉)
Large Language Models (LLM's) have proven to be useful for numerous tasks. LLM's can summarise text, generate text, classify text or translate text. What LLM's can also be used for is converting unstructured data to structured data.
Scaling up: bringing your Azure DevOps CI/CD setup to the next level 🚀 (on Xebia.com ⧉)
Azure DevOps pipelines are a great way to automate your CI/CD process. But what if you have many projects? In this blog post, we will show you how you can scale up your Azure DevOps CI/CD setup for reusability and easy maintenance.
PyData Eindhoven 2023
Eindhoven, The Netherlands —
LLM data extraction: prompt engineering, JSON output modes, Function calling, Pydantic schemas, evaluation and a GPT 3.5 vs GPT 4 vs PaLM showdown.
GoDataFest 2023
Amsterdam, The Netherlands —
How can we extract more value from data by using what LLMs can offer us? Previously impossible data extractions can be now done and a new level of data quality and direct filtering can now be realized.
DataMass Gdańsk Summit 2023
Gdańsk, Poland —
Enriching datasets with LLMs: JSON output modes, schema definitions with Pydantic, evaluating structured data extraction, Function Calling.
