Showing 4 open source projects for "summarize"

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    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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    Fully Managed MySQL, PostgreSQL, and SQL Server

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  • 1
    Shapash

    Shapash

    Explainability and Interpretability to Develop Reliable ML models

    Shapash is a Python library dedicated to the interpretability of Data Science models. It provides several types of visualization that display explicit labels that everyone can understand. Data Scientists can more easily understand their models, share their results and easily document their projects in an HTML report. End users can understand the suggestion proposed by a model using a summary of the most influential criteria.
    Downloads: 0 This Week
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  • 2
    cracking-the-data-science-interview

    cracking-the-data-science-interview

    A Collection of Cheatsheets, Books, Questions, and Portfolio

    ...The project organizes content across many fundamental areas of data science, including statistics, probability, SQL, machine learning, and deep learning. It includes cheat sheets that summarize important technical concepts commonly discussed during technical interviews. The repository also provides links to recommended books, tutorials, practice platforms, and blog posts that help learners strengthen their theoretical and practical skills. In addition to conceptual study materials, the project includes interview question banks and case study prompts that simulate real hiring scenarios. ...
    Downloads: 0 This Week
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  • 3
    ktrain

    ktrain

    ktrain is a Python library that makes deep learning AI more accessible

    ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines...
    Downloads: 0 This Week
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  • 4
    AI Cheatsheets

    AI Cheatsheets

    Essential Cheat Sheets for deep learning and machine learning research

    ...It compiles cheat sheets for widely used libraries and technologies such as TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Matplotlib, and PySpark. These materials summarize common functions, workflows, and best practices in a concise visual format that makes them easy to consult during development or study sessions. The repository functions as a centralized library where users can quickly access reference materials for both machine learning theory and practical programming tools. Many of the cheat sheets are available as downloadable PDFs and images, allowing learners to keep them as quick references while working on projects.
    Downloads: 0 This Week
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  • Host LLMs in Production With On-Demand GPUs Icon
    Host LLMs in Production With On-Demand GPUs

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    Deploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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