The Conference for Machine Learning Innovation

Doing More with Less: Building Machine Learning Solutions without Large Labeled Datasets

Session
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✓ 10 % Team Discount
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Join the ML Revolution!
Register until the conference starts:
✓ 2-in-1 conference special
✓ 10 % Team Discount
Register Now
Join the ML Revolution!
Register until August 12:
✓ML Intro Day for free
✓Save up to $380
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Join the ML Revolution!
Register until August 12:
✓ML Intro Day for free
✓Save up to $380
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Infos

Data is the fuel behind machine learning solutions but also its biggest weakness. The dependency on large labeled datasets makes many machine learning processes completely unpractical. How can organizations address this challenge? This session presents a series of techniques that can help companies build machine learning solutions in the absence of large labeled datasets. Exploring methods such as semi-supervised, weakly-supervised or reinforcement learning to different privacy techniques, we explore patterns and neural network architectures that work efficiently in scenarios without large labeled datasets. To keep things practical we will discuss several case studies that illustrate how these methods are being used in real-world machine learning solutions today.

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

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

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

Behind the Tracks