Residing between supervised and unsupervised learning, semi-supervised learning accepts data that’s partially labeled or where the majority of the data lacks labels.

Describe text classification and related terminology (e.g., supervised machine learning). Apply text classification to marketing data through a peer-graded project. Apply text classification to a ...

A research team from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences has released ...

This week we will learn about non-parametric models. k-Nearest Neighbors makes sense on an intuitive level. Decision trees are a supervised learning model that can be used for either regression or ...

This week, I debated with my friend whether one should consider that Generative AI tools are created through supervised or unsupervised learning. At the end of it, I lost the debate.

The AI model can learn from data that’s already out there, without any special labels. Self-supervised learning enables pre-training an AI model on massive amounts of general-purpose data. That way, ...

More information: Qingyuan He et al, Exploring Unlabeled Data in Multiple Aspects for Semi-Supervised MRI Segmentation, Health Data Science (2024). DOI: 10.34133/hds.0166 ...

U. Jo and S. B. Kim, “Semi-Supervised Learning with Wafer-Specific Augmentations for Wafer Defect Classification,” in IEEE Access, doi: 10.1109/ACCESS.2024.3522180. Tags: data augmentation defect ...