Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Jinsong Yu shares deep architectural insights ...

A production-ready microservices architecture for NLP text processing built with FastAPI and gRPC. - bltzr75/text-processing-microservices ...

Abstract: Deep learning models have greatly improved various natural language processing tasks. However, their effectiveness depends on large data sets, which can be difficult to acquire. To mitigate ...

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When you’re working with AI and natural language processing, you’ll quickly encounter two fundamental concepts that often get confused: tokenization and chunking. While both involve breaking down text ...

Unlock automatic understanding of text data! Join our hands-on workshop to explore how Python—and spaCy in particular—helps you process, annotate, and analyze text. This workshop is ideal for data ...

Real world analysis of VTE incidence in lung cancer: A comprehensive assessment of the Khorana score and other clinical factors in predicting VTE incidence. This is an ASCO Meeting Abstract from the ...

Background: Free-text comments in patient-reported outcome measures (PROMs) data provide insights into health-related quality of life (HRQoL). However, these comments are typically analysed using ...