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Areas Served: ![Is it possible to do Text Classification on unlabeled data? (Feat. Zero-Shot Classification) [Experiment]](https://i0.wp.com/miro.medium.com/v2/resize:fit:875/0*3WFE40xpkt2gMo3Q?w=875&resize=875,584&ssl=1 "Is it possible to do Text Classification on unlabeled data? (Feat. Zero-Shot Classification) [Experiment]")
Is it possible to do Text Classification on unlabeled data? (Feat. Zero-Shot Classification) [Experiment]
Author(s): Ala Alam Falaki Originally published on Towards AI. Photo by Markus Spiske on Unsplash A couple of months ago, I did an experiment to answer the question: Is it possible to do sentiment analysis if we do not have the target …
Empowering Computer Vision with Zero-Shot Learning in the Data-Centric Small Data Age
Author(s): Luhui Hu Originally published on Towards AI. Photo by Jeremy Perkins on Unsplash Inside zero-shot learning from OpenAI CLIP, Microsoft RegionCLIP, and Meta SAM The era of big data has provided Machine Learning (ML) and Computer Vision (CV) with ample fuel …
SAM: A Image Segmentation Foundation Model
Author(s): Poojatambe Originally published on Towards AI. Segment Anything Model by Facebook’s Meta AI Research SAM With new advances in Generative AI, large-scale models called foundation models are developed. The foundation models are trained on a massive amount of unannotated data and …
Automating Zero-Shot Classification Generating Model Labels with GPT-3
Author(s): Carlo Borella Originally published on Towards AI. Source: Image generated by the author using MidJourney Zero-shot learning is a machine learning method that allows using a pre-trained model to classify data according to a set of classes or labels that have …
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