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    Build Agents and Models on One Platform

    Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

    Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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    MongoDB Atlas runs apps anywhere

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    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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    Common Resource Grep - crgrep

    Common Resource Grep - crgrep

    Common Resource Grep

    CRGREP searches for matching text in databases, various document formats, archives and other difficult to access resources. A command line tool for name and content text matching in database tables, plain files, MS Office documents, PDF, archives, MP3 audio, image meta-data, scanned documents, maven dependencies and web resources. CRGREP will search resources within resources of any arbitrary combination or depth, so text within a document within a zip archive, and so on. Here you...
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  • 2
    CC-Net

    CC-Net

    Tools to download and cleanup Common Crawl data

    cc_net provides tools to download, segment, clean, and filter Common Crawl to build large-scale text corpora, including monolingual datasets and the multilingual CC-100 collection introduced in the associated paper. It includes pipelines to fetch snapshots, extract text, de-duplicate, identify language, and apply quality filtering based on heuristics and language models. The outputs are intended for pretraining language models and for creating standardized corpora that can be reproduced or updated with new crawls. ...
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  • 3

    Natural Language Analysis with Ngrams

    NLP tool for statistical analysis of words, sentences, documents

    ...I will JAR-it once I decide that it can be called a final release. This project was made by creating a corpus from the Google Ngrams data for English Language, version 20120701. EOWL list of English words was used to filter-out the words from Ngrams data. For each year, per word, the data was added and calculated to describe the average appearance of a word per document for a given year. Before using this program, you MUST download the corpus.
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