The Levels of RAG (on Xebia.com ⧉)
LLM’s can be supercharged using a technique called RAG, allowing us to overcome dealbreaker problems like hallucinations or no access to internal data. But what can we expect from RAG? What use cases work well and which are more challenging? Let’s find out together!
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!
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.
How to create a Devcontainer for your Python project 🐳 (on Xebia.com ⧉)
Instead of giving other developers a setup document, let’s make sure we also create formal instructions so we can automatically set up the development environment. Devcontainers let us do exactly this.
pyspark-bucketmap
pyspark-bucketmap is a tiny module for pyspark which allows you to bucketize DataFrame rows and map their values easily.
DropBlox: Coding Challenge at PyCon DE & PyData Berlin 2022 (on Xebia.com ⧉)
Conferences are great. You meet new people, you learn new things. But have you ever found yourself back in the hotel after a day at a conference, thinking what to do now? Or were you ever stuck in one session, wishing you had gone for that other one?
From Linear Regression to Neural Networks
How are linear regression, logistic regression and neural networks related? What is overfitting and how do we fight it? In this post, we find answers to these questions in an interactive way by working with a real-world dataset on penguins.
Making Art with Generative Adversarial Networks
Can computers make art? To find out, we tried ourselves. We used Generative Adversarial Networks to try to paint new Van Gogh paintings.
Finding 'God' components in Apache Tika
How did big, bulky software components come into being? In this project, we explore the evolution of so-called God Components;
