Dataiku Technical Ebook

Top Data Labeling Techniques

For Better Predictions and Improved Model Accuracy

While they are unique and each come with their own set of benefits and challenges, the data labeling techniques of semi-supervised learning (SSL) and active learning can be used to perform predictions and improve model accuracy. This technical ebook breaks down both approaches.
DTKU_Unpacking-Data-Labelling_Ebook_WEB.pdf

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Bootstrapping a Data Science Project With Unlabeled Data

This Ebook Will:

  • Present an overview of three popular active learning packages and how they compare

  • Explore if using the confidence of a semi-supervised model to select samples to be pseudo-labeled outperforms a fixed size selection or not

  • Discover findings from a reproduction exercise based on results from the 2019 paper "Diverse Mini-Batch Active Learning"

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