The Conference for Machine Learning Innovation

Lean Data Science: Tailoring Agile Practices for Data Science Projects

Session
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Register until October 20:
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✓ Team discount
✓ Extra Specials for Freelancers
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Join the ML Revolution!
Register until October 20:
✓ Save up to $233
✓ Team discount
✓ Extra Specials for Freelancers
Register Now
Join the ML Revolution!
Register until November 03:
✓ Save up to €494
✓ 10% Team Discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Register until November 03:
✓ Save up to €494
✓ 10% Team Discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now
Infos

About 80% of AI projects never make it into production.

Why do they fail? Top factors are misaligned objectives, lack of collaboration between business stakeholders and data scientists, and an inability to leverage the collective knowledge and talents of the entire “team”, including Data Scientists, Data Engineers, ML Ops, etc.

These problems are not unique. Agile practices have become the de-facto approach to deliver software applications effectively. Can we adapt them for data science projects?

It is not that easy. Most data science teams experience problems adapting Agile due to Data Science specifics. For example, they struggle to produce a valuable increment at the end of the sprint, sometimes newly discovered information can ruin a sprint plan right in the middle of it, etc.

We need to tailor Agile Practices to allow for Data Science specifics.

In this talk, we will explore collaborative techniques that guide data science teams in their agile adaption. We will discuss how to come up with nice and clear product hypothesis, how to prioritize them using ICE/RICE method, how to decompose huge AI Epics into a small and easy to validate data science hypothesis, and how to effectively manage work using Kanban and Scrum approaches.

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Singapore Singapore .

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Berlin Berlin .

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Munich Munich .

This Session Diese Session originates from the archive of stammt aus dem Archiv von MunichMunich . Take me to the current program of . Hier geht es zum aktuellen Programm von Singapore Singapore , Berlin Berlin or oder Munich Munich .

Behind the Tracks