Scaling An ML Team (10–100+ People)

Game of Thrones

This is the second part of our series on scaling ML teams! Read on if you’re a leader in an ML team that is starting to grow beyond 10 people and scale from one team to a collection of teams working on the ML pipeline. If you’re a smaller team or you haven’t seen our first post on scaling from 0–10 people, you may want to read that first.

Read More

Scaling an ML Team (0–10 People)

Team against skyline

So you’re doing an ML project! Maybe you want to build an object detection system for a robotics application or you want to add a recommender system to your webapp. You’ll need a team to build and improve this ML system. In the beginning, this can be a single (very stressed) engineer hacking together an MVP, but it can evolve into an entire department with highly specialized teams and hundreds of people. At each stage of developing a model pipeline, you will encounter different problems that require different team structures to overcome.

Read More

10 Data Visualisation Tools every Data Engineer has to know in 2020

Have you ever bought any home appliance only to find that you already have one buried somewhere deep within the basement, just under a box of Christmas lights? It is nearly as annoying as collecting data without knowing what knowledge they hide. That’s why delivering data visualization tools supports all companies and teams, be that marketing, accounting, data science, or business development.

Read More