How to Reduce Data Labeling Costs (+ Increase Data Quality) With Active Learning

Presented by

Alexandre Abraham and Léo Dreyfus-Schmidt, Research Scientists at Dataiku

About this talk

Many times, businesses have a myriad of data issues which often stem from a lack of data governance within the organization. Before any algorithms run or models are deployed, there is a need for high-quality, labeled data. In this webinar, Dataiku’s very own Research Scientists Alexandre Abraham and Leo Dreyfus-Schmidt explain the importance of active learning and how it can be used to lower the cost of data labeling necessary to reach a given model’s accuracy.

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Dataiku is the world’s leading platform for Everyday AI, systemizing the use of data for exceptional business results. Organizations that use Dataiku elevate their people (whether technical and working in code or on the business side and low- or no-code) to extraordinary, arming them with the ability to make better day-to-day decisions with data. More than 450 companies worldwide use Dataiku to systemize their use of data and AI, driving diverse use cases from fraud detection to customer churn prevention, predictive maintenance to supply chain optimization, and everything in between.