JAX & W-JAX
Die Konferenzen für Java, Architektur- und Software-Innovation

Agile Machine Learning: from Theory to Production

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Infos
Dienstag, 7. November 2017
15:00 - 16:00
Raum:
Garmisch

Artificial Intelligence (AI) and Machine Learning (ML) are all the rage right now. In this session, we’ll be looking at engineering best practices that can be applied to ML, how ML research can be integrated with an agile development cycle, and how open ended research can be managed within project planning According to a recent Narrative Science survey, 38 per cent of enterprises surveyed were already using AI, with 62 per cent expecting to be using it by 2018. So it’s understandable that many companies might be feeling the pressure to invest in an AI strategy, before fully understanding what they are aiming to achieve, let alone how it might fit into a traditional engineering team or how they might get it to a production setting. At Basement Crowd we are currently taking a new product to market and trying to go from a simple idea to a production ML system. Along the way we have had to integrate open ended academic research tasks with our existing agile development process and project planning, as well as working out how to deliver the ML system to a production setting in a repeatable, robust way, with all the considerations expected from a normal software project.

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

This Session Diese Session originates from the archive of stammt aus dem Archiv von W-JAXW-JAX . Take me to the current program of . Hier geht es zum aktuellen Programm von W-JAX W-JAX or oder JAX JAX .
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