Showing 5 open source projects for "unstructured data"

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    Gemini 3 and 200+ AI Models on One Platform

    Access Google's best plus Claude, Llama, and Gemma. Fine-tune and deploy from one console.

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    AI-powered service management for IT and enterprise teams

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  • 1
    RAGFlow

    RAGFlow

    RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine

    RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
    Downloads: 7 This Week
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  • 2
    Diffgram

    Diffgram

    Training data (data labeling, annotation, workflow) for all data types

    ...Training Data is the art of supervising machines through data. This includes the activities of annotation, which produces structured data; ready to be consumed by a machine learning model. Annotation is required because raw media is considered to be unstructured and not usable without it. That’s why training data is required for many modern machine learning use cases including computer vision, natural language processing and speech recognition.
    Downloads: 4 This Week
    Last Update:
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  • 3
    MindsDB

    MindsDB

    Making Enterprise Data Intelligent and Responsive for AI

    MindsDB is an AI data solution that enables humans, AI, agents, and applications to query data in natural language and SQL, and get highly accurate answers across disparate data sources and types. MindsDB connects to diverse data sources and applications, and unifies petabyte-scale structured and unstructured data. Powered by an industry-first cognitive engine that can operate anywhere (on-prem, VPC, serverless), it empowers both humans and AI with highly informed decision-making capabilities. ...
    Downloads: 0 This Week
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  • 4
    Pytorch Points 3D

    Pytorch Points 3D

    Pytorch framework for doing deep learning on point clouds

    Torch Points 3D is a framework for developing and testing common deep learning models to solve tasks related to unstructured 3D spatial data i.e. Point Clouds. The framework currently integrates some of the best-published architectures and it integrates the most common public datasets for ease of reproducibility. It heavily relies on Pytorch Geometric and Facebook Hydra library thanks for the great work! We aim to build a tool that can be used for benchmarking SOTA models, while also allowing practitioners to efficiently pursue research into point cloud analysis, with the end goal of building models which can be applied to real-life applications. ...
    Downloads: 0 This Week
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    MongoDB Atlas runs apps anywhere

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  • 5
    TEXT2DATA

    TEXT2DATA

    Text Analytics Platform

    Bring Text Analytics Platform that uses NLP (Natural Language Processing) and Machine Learning to your work environment. Extract essential information from your text documents and let Artificial Intelligence save your time. Get detailed and agile reports on your unstructured data.
    Downloads: 0 This Week
    Last Update:
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