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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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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. Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Getir is the pioneer of ultrafast grocery delivery.

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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. To perform this, extractive summarization methods like tf-idf, and text-rank algorithms have been used. At this point, datasets like […]

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Meet the Winners of the Youth Mental Health Narratives Challenge

DrivenData Labs

I generated unlabeled data for semi-supervised learning with Deberta-v3, then the Deberta-v3-large model was used to predict soft labels for the unlabeled data. The semi-supervised learning was repeated using the gemma2-9b model as the soft labeling model. Then we leveraged the benefits of NLP algorithms (e.g.,

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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.

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MLOps and the evolution of data science

IBM Journey to AI blog

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?