Categories: AI/ML Research

Feature Engineering with LLM Embeddings: Enhancing Scikit-learn Models

Large language model embeddings, or LLM embeddings, are a powerful approach to capturing semantically rich information in text and utilizing it to leverage other machine learning models โ€” like those trained using Scikit-learn โ€” in tasks that require deep contextual understanding of text, such as intent recognition or sentiment analysis.
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Workflow upscale/magnify video from Sora with Wan , based on cseti007

๐Ÿ“ฆ : https://github.com/lovisdotio/workflow-magnify-upscale-video-comfyui-lovis I did this ComfyUI workflow for Sora 2 upscaling ๐Ÿš€ ( or…

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The Complete Guide to Pydantic for Python Developers

Python's flexibility with data types is convenient when coding, but it can lead to runtime…

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Rooms from Motion: Un-posed Indoor 3D Object Detection as Localization and Mapping

We revisit scene-level 3D object detection as the output of an object-centric framework capable of…

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Inside the AIPCon 8 Demos Transforming Manufacturing, Insurance, and Construction

Editorโ€™s Note: This is the second in a two-part series highlighting demo sessions from AIPCon…

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Responsible AI design in healthcare and life sciences

Generative AI has emerged as a transformative technology in healthcare, driving digital transformation in essential…

21 hours ago

5 ad agencies used Gemini 2.5 Pro and gen media models to create an “impossible adโ€

The conversation around generative AI in the enterprise is getting creative.ย  Since launching our popular…

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