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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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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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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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LLM distillation demystified: a complete guide

Snorkel AI

Data science teams that want to further reduce the need for human labeling can employ supervised or semi-supervised learning methods to relabel likely-incorrect records based on the patterns set by the high-confidence data points.

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LLM distillation demystified: a complete guide

Snorkel AI

Data science teams that want to further reduce the need for human labeling can employ supervised or semi-supervised learning methods to relabel likely-incorrect records based on the patterns set by the high-confidence data points.

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MLOps and the evolution of data science

IBM Journey to AI blog

The term was originally coined in 2015 in a published research paper called, “Hidden Technical Debts in the Machine Learning System,” which highlighted common problems that arose when using machine learning for business applications. Foundation models aim to solve this problem.