Xavier Geerinck

Azure Project Bonsai - Physical CartPole Project

In my previous post I revisited the Bonsai platform. Now it's time to actually start preparing to put it into production! (this will become more clearer over time 😉) To start off with a spoiler: Project Bonsai - It's impressive! 😎

The Azure Project Bonsai Platform Revisited

Schedule Kubernetes CronJob to restart pods automatically

For a project I needed a way to automatically schedule pods to be deleted every 3 hours. This was due to the nature of the project where we wanted a cleanup in memory due to zombie processes appearing. It's not a clean fix, but it was necessary for production to run stable while we were patching things.

Tutorial - Creating an Email Microservice with Typescript and Dapr

How to set up a Typescript Project with Yeoman

Typescript is quite cumbersome to set-up... it's not built in in Node.js but it is important to write stable code with type checking. Since I write a lot of Typescript projects, it's quite handy to have an explanation on how to set-up a typescript project quickly.

Gradually adopting Autonomous Systems in Production

Reinforcement Learning is something I have been covering a while now! Lately, I have seen this space growing tremendously but keep on seeing the same issue arising each time: "How can I as a company with an existing infrastructure / applications (= brownfield) adopt Reinfocement Learning?"

Analyzing ML/RL Model Performance with Azure Synapse Analytics Spark Pools

I have been following Azure Synapse Analytics since it was still in development and the mock-ups were not finished yet. The vision that Azure Synapse Analytics brings is simply amazing, bringing an End-to-End analytics platform that seamlessly mixes SQL Dedicated, SQL On-Demand, and Spark to prepare, analyze and publish your data needs.

Machine Learning Operations - MLOps explained

MLOps is the continuation of DevOps, extended for Machine Learning. It allows data scientists, data engineers, application developers, and the operations team to collaborate, reducing the time from model creation towards first production deployment.

Creating a Raspberry PI Cluster (1 Raspberry Pi & 4 Pi Zeros) with Cluster Hat