Showing 2 open source projects for "code block"

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    Skillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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  • Teradata VantageCloud Enterprise is a data analytics platform for performing advanced analytics on AWS, Azure, and Google Cloud. Icon
    Teradata VantageCloud Enterprise is a data analytics platform for performing advanced analytics on AWS, Azure, and Google Cloud.

    Power faster innovation with Teradata VantageCloud

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  • 1
    Aniseed

    Aniseed

    Neovim configuration and plugins in Fennel (Lisp compiled to Lua)

    ...Allowing you to easily write plugins or configurations in a Clojure-like Lisp with great runtime performance. For interactive evaluation, you need to install Conjure as well. It’ll allow you to send portions of your code off for evaluation as well as see the results in an interactive log buffer. Aniseed ships with a set of module macros that make interactive evaluation not only possible but rich and intuitive. You should read:h aniseed to learn the details but it’s worth mentioning that you opt-in by starting your file with a (module …​) block, you then export values from your module with the (def…​) macros.
    Downloads: 6 This Week
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  • 2
    ResNeXt

    ResNeXt

    Implementation of a classification framework

    ...Instead of simply increasing depth or width, ResNeXt introduces a new dimension called cardinality, which refers to the number of parallel transformation paths (i.e. the number of “branches”) that are aggregated together. Each branch is a small transformation (e.g. bottleneck block) and their outputs are summed—this enables richer representation without excessive parameter blowup. The design is modular and homogeneous, making it relatively easy to scale (by tuning cardinality, width, depth) and adopt in existing residual frameworks. The official repository offers a Torch (Lua) implementation with code for training, evaluation, and pretrained models on ImageNet. ...
    Downloads: 0 This Week
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