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Counting shots, making strides: Zero, one and few-shot learning unleashed 

Data Science Dojo

Zero-shot, one-shot, and few-shot learning are redefining how machines adapt and learn, promising a future where adaptability and generalization reach unprecedented levels. Source: Photo by Hal Gatewood on Unsplash In this exploration, we navigate from the basics of supervised learning to the forefront of adaptive models.

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Data Science Dojo - Untitled Article

Data Science Dojo

Zero-shot, one-shot, and few-shot learning are redefining how machines adapt and learn, promising a future where adaptability and generalization reach unprecedented levels. Source: Photo by Hal Gatewood on Unsplash In this exploration, we navigate from the basics of supervised learning to the forefront of adaptive models.

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Big Data – Das Versprechen wurde eingelöst

Data Science Blog

Die vollautomatisierte Analyse von textlicher Sprache, von Fotos oder Videomaterial war 2015 noch Nische, gehört heute jedoch zum Alltag hinzu. Während 2015 noch von neuen Geschäftsmodellen mit Big Data geträumt wurde, sind Data as a Service und AI as a Service heute längst Realität! ChatGPT basiert auf GPT-3.5

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Modern NLP: A Detailed Overview. Part 2: GPTs

Towards AI

Semi-Supervised Sequence Learning As we all know, supervised learning has a drawback, as it requires a huge labeled dataset to train. In 2015, Andrew M. As supervised learning required huge datasets for image processing to train super-deep models, the scarcity of data became an issue.

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Conformer-2: a state-of-the-art speech recognition model trained on 1.1M hours of data

AssemblyAI

We have begun to observe diminishing returns and are already exploring other promising research directions into multimodality and self-supervised learning. While this progress has been exciting, bootstrapping strong teacher models was bound to run into an asymptotic limit and stop bearing fruit. Panayotov, G. Povey and S.

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Getir end-to-end workforce management: Amazon Forecast and AWS Step Functions

AWS Machine Learning Blog

Getir was founded in 2015 and operates in Turkey, the UK, the Netherlands, Germany, and the United States. Given the availability of diverse data sources at this juncture, employing the CNN-QR algorithm facilitated the integration of various features, operating within a supervised learning framework.

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Foundation models: a guide

Snorkel AI

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning? Self-supervised learning is a kind of machine learning that creates labels directly from the input data. Find out in the guide below.