/ Recent content on neoxone.com Hugo -- gohugo.io en-us Thu, 15 May 2025 00:00:00 +0000 /2025/05/15/kettlegrok-v1/ Thu, 15 May 2025 00:00:00 +0000 /2025/05/15/kettlegrok-v1/ Workout Plan Overview Duration: ~30 minutes per session (including warm-up and cool-down) Frequency: 6 days a week Intensity: High, focusing on strength and cardio Structure: Warm-up: 5 minutes of dynamic stretches (e.g., arm circles, leg swings, torso twists) Main Workout: 3 sets of each exercise with specified reps or time, following tempo guidelines Cool-down: 5 minutes of static stretches (e.g., hamstring stretch, chest opener, quad stretch) Total Time: Approximately 30 minutes Daily Workout Plan Day 1: Upper Body Push and Core Targets: Shoulders, pecs, triceps, core Exercises: Kettlebell Bench Press Weight: 2x24kg (one per hand) /2021/09/28/r-basic-tips-for-production-code/ Tue, 28 Sep 2021 00:00:00 +0000 /2021/09/28/r-basic-tips-for-production-code/ h3 { margin-left: -24px; } Disclaimer : No need to follow all the rules, tips and tricks you read. You are still the best judge when it comes to writing code. Context is a huge factor and you should not rely on any particular advice. Start by writing something that works. It does not need to be perfect. 1. Microbench for performance critical code. Every decision is a trade off in production. /2021/01/31/plumber-v1-0-showcase-part-1/ Sun, 31 Jan 2021 00:00:00 +0000 /2021/01/31/plumber-v1-0-showcase-part-1/ When I discovered plumber, I fell in love with its versatility. With version 1.0, it is even more versatile and modular than before. Since I had the chance to contribute to the project, I wanted to share some of the new features that made it into this release. Part 1 New annotation @plumber New tags were introduced in 1.0. @plumber allows users to interact with the router object during its creation process. /2020/12/12/deploying-r-api-in-production/ Sat, 12 Dec 2020 00:00:00 +0000 /2020/12/12/deploying-r-api-in-production/ Back in 2018, I had to deploy an R API on kubernetes. It lead to a quick presentation at R à Québec 2019 which is still available here. Since then, I deployed half a dozen more solutions while refining the deployment pipeline. In my opinion, R is a vary viable solution as the stack stays the same through the whole data science cycle. This is more or less the workflow I use. /about/ Thu, 05 May 2016 21:48:51 -0700 /about/ I’m a formally credentialed casualty actuary, doing mostly devops and solution engineering in data science. As an old and wise actuary once said, “Aren’t we all data scientist?”. Like many in my fields, I have dabbled in quite a diverse selection of technologies, getting decent with a dozen or so. For everything else, I have a brain and a search engine. Most recently, my main focus has been to prove the viability of R Language based solutions in the insurance industry.