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Data Labeling for Machine Learning: Market Overview, Approaches, and Tools

KDnuggets

So much of data science and machine learning is founded on having clean and well-understood data sources that it is unsurprising that the data labeling market is growing faster than ever.

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Data Labeling for Machine Learning: Market Overview, Approaches, and Tools

KDnuggets

So much of data science and machine learning is founded on having clean and well-understood data sources that it is unsurprising that the data labeling market is growing faster than ever.

professionals

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It’s time to shelve unused data

Dataconomy

Artificial intelligence (AI) can be used to automate and optimize the data archiving process. There are several ways to use AI for data archiving. This process can help organizations identify which data should be archived and how it should be categorized, making it easier to search, retrieve, and manage the data.

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MLCoPilot: Empowering Large Language Models with Human Intelligence for ML Problem Solving

Towards AI

This code can cover a diverse array of tasks, such as creating a KMeans cluster, in which users input their data and ask ChatGPT to generate the relevant code. In the realm of data science, seasoned professionals often carry out research to comprehend how similar issues have been tackled in the past.

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