Showing 7 open source projects for "machine learning"

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  • Context for your AI agents Icon
    Context for your AI agents

    Crawl websites, sync to vector databases, and power RAG applications. Pre-built integrations for LLM pipelines and AI assistants.

    Build data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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  • 1
    Deepchecks

    Deepchecks

    Test Suites for validating ML models & data

    Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate your model and evaluate it. ...
    Downloads: 0 This Week
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  • 2
    APIAuto

    APIAuto

    The most advanced tool for HTTP API

    The most powerful and easy-to-use HTTP interface tool for agile development, machine learning zero-code testing, code generation and static inspection, document generation and cursor suspension comments. A one-stop experience integrating documentation, testing, mocking, debugging, and management, as well as efficient and easy-to-use shortcut keys such as one-key formatting, commenting/uncommenting, etc. In terms of common functions, it far exceeds Postman, Swagger, YApi and other open-source and commercial API documentation/testing tools, and can import use cases and documents with one click. ...
    Downloads: 0 This Week
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  • 3
    LoopVectorization.jl

    LoopVectorization.jl

    Macro(s) for vectorizing loops

    ...It analyzes loops and generates highly efficient code that leverages CPU vector instructions, making it ideal for performance-critical computing in fields such as scientific computing, signal processing, and machine learning.
    Downloads: 1 This Week
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  • 4
    nbmake

    nbmake

    Pytest plugin for testing notebooks

    Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks.
    Downloads: 0 This Week
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  • DAT Freight and Analytics - DAT Icon
    DAT Freight and Analytics - DAT

    DAT Freight and Analytics operates DAT One truckload freight marketplace

    DAT Freight & Analytics operates DAT One, North America’s largest truckload freight marketplace; DAT iQ, the industry’s leading freight data analytics service; and Trucker Tools, the leader in load visibility. Shippers, transportation brokers, carriers, news organizations, and industry analysts rely on DAT for market trends and data insights, informed by nearly 700,000 daily load posts and a database exceeding $1 trillion in freight market transactions. Founded in 1978, DAT is a business unit of Roper Technologies (Nasdaq: ROP), a constituent of the Nasdaq 100, S&P 500, and Fortune 1000. Headquartered in Beaverton, Ore., DAT continues to set the standard for innovation in the trucking and logistics industry.
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  • 5

    Taylorplot_Neptune

    Creation of a Taylorplot for several machine learning models

    Here we present the lines of code for creating a taylor plot with python to display several machine learning models. We show the solution for displaying 10 models, but the list and number can be changed simply by modifying the sample list.
    Downloads: 0 This Week
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  • 6
    Frontend Regression Validator (FRED)

    Frontend Regression Validator (FRED)

    Visual regression tool used to compare baseline and updated instances

    ...The visual analysis computes the Normalized Mean Squared error and the Structural Similarity Index on the screenshots of the baseline and updated sites, while the visual AI looks at layout and content changes independently by applying image segmentation Machine Learning techniques to recognize high-level text and image visual structures. This reduces the impact of dynamic content yielding false positives. FRED is designed to be scalable. It has an internal queue and can process websites in parallel depending on the amount of RAM and CPUs (or GPUs) available.
    Downloads: 0 This Week
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  • 7

    Chronological Cohesive Units

    The experimental source code for the paper

    The experimental source code for the paper, "A Novel Recommendation Approach Based on Chronological Cohesive Units in Content Consuming"
    Downloads: 0 This Week
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