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Exploring mental well-being insights with zero-shot classificationArtwork by Vivian Peng — reposted with permissionSentiment analysis is a powerful tool in natural language processing (NLP) for exploring public opinions and emotions in text. In the context of mental health, it can provide compelling insights into the holistic wellness of individuals. As a summer data science associate at The Rockefeller Foundation, I conducted a research project using NLP techniques to explore Reddit discussions on depression before and…

Part 2 — Visual classification via Description from LLMsContinue reading on Towards Data Science » Part 2 — Visual classification via Description from LLMsContinue reading on Towards Data Science » FOLLOW US ON GOOGLE NEWS Read original article here Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners, all materials…

Using LLMs to obtain labels for supervised modelsPhoto by h heyerlein on UnsplashLabeling data is a critical step in building supervised machine learning models, as the quantity and quality of labels is often the main factor that determines model performance.However, labeling data can be very time-consuming and expensive, especially for complex tasks that involve domain knowledge or reading large amounts of data.In recent years, large language models (LLMs) have emerged as a powerful solution for obtaining labels on text…

Absci founder Sean McClain, left, chief innovation officer Andreas Busch, center, and AI lead Joshua Meier are confident that generative AI programs will lead to antibodies with high efficacy in binding to disease targets. The company will have drugs in the clinic using the method next year, says McClain. Tiernan Ray/ZDNET"We're really excited because we will have a drug in the clinic in 2024 that will utilize this technology," said Absci founder and CEO Sean McClain, in the same interview with Meier. "It'll be the…

An evaluation of unsupervised text classification approachesImage by Gertrūda Valasevičiūtė on UnsplashThis post is based on our NLPIR 2022 paper “Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches”. You can read more details there.Unsupervised text classification approaches aim to perform categorization without using annotated data during training and therefore offer the potential to reduce annotation costs💰. Generally, unsupervised text classification approaches aim to map text to…