May 08, 2021
Kubernetes is a tool. The concepts that are around this one are interesting. Zero downtime deployment, containers orchestration, scaling, etc. They help to deploy safely and then to get solid ML systems. It's relevant to understand these concepts. This week, I would like to highlight some of them through different resources.
Apr 20, 2021
Recently, for an R&D project, I had to implement Bayesian AB tests. As AB tests are an important key to develop safely and surely, I decided to present to you what I've learnt so far. I focused my reasearch on the Pymc3 library.
Mar 15, 2021
I'm glad to see that we can find more and more papers about deploying Machine Learning. Challenges are multiple and everywhere. Let's dive a bit into these challenges and resources that discuss these.
Mar 09, 2021
Data are the food of machine learning training. There are more and more data everyday. But most of the time, these data are unlabelled. Labelling them manually is expensive and boring.
There are different ways to tackle this problem.
Active learning Active learning optimises labelling. It extracts the data that must be labelled.
The system requests a manual labelling for identified cases. Those depend on the strategy you choose. I will cover only two of these strategies.
Mar 01, 2021
Code standardisation with Pylint, container orchestration with Kubernetes, lakehouse with DeltaLake, working with cats <3, these are many concepts that can be useful to productionalize machine learning. This is what I saw recently and thought interesting.