A fable about a company's journey through scaling their ML function, and some practical advice on how you should do it| Alexandru Burlacu
My experience interviewing for a few Senior ML and MLOps roles. You will learn what are the common steps, quirks, and tips how to nail an interview for senior ML engineer positions.| Alexandru Burlacu
How to pick a tool, language, or framework when real money and the business is at stake. What to consider when faced with this kind of situation.| Alexandru Burlacu
Some advice how to grow to a senior engineering role. What skills are most valuable for a senior software engineering career, and how to aquire them.| Alexandru Burlacu
When deploying machine learning algorithms, the stakes are much higher than in any toy problem or competition. For this reason, we need a much more thorough evaluation of our models, to make sure it is indeed good.| Alexandru Burlacu
K-Means is an interesting, simple, and pretty intuitive algorithm. It turns out it can do more than just clustering, for example classification.| Alexandru Burlacu
When it comes to production-ready systems we need a way to know what’s going on in it, aiding us in debugging it, when the time comes.| Alexandru Burlacu
Find out how working on an independent research project led me to apply my MLOps skills to create a performant and cost-effective experiment infrastructure| alexandruburlacu.github.io
It’s important to be able to deploy a machine learning model when trained. But how do we approach serving ML models correctly?| alexandruburlacu.github.io
AutoML sounds like magic. But how effective is it? And when to better use a simpler approach?| alexandruburlacu.github.io