Showing 2 open source projects for "code block installer"

View related business solutions
  • No-code email and landing page creation Icon
    No-code email and landing page creation

    Make campaign creation fast and easy with Knak

    Built for speed and collaboration, Knak streamlines campaign production with modular templates, real-time editing, simple collaboration, and seamless integrations with leading MAPs like Adobe Marketo Engage, Salesforce Marketing Cloud, Oracle Eloqua, and more. Whether you're supporting global teams or launching fast-turn campaigns, Knak helps you go from brief to build in minutes—not weeks. Say goodbye to bottlenecks and hello to marketing agility.
    Learn More
  • Hightouch is a data and AI platform for marketing and personalization. Icon
    Hightouch is a data and AI platform for marketing and personalization.

    Marketing needs data and AI. Give them Hightouch.

    Find insights, run real-time campaigns, and build AI agents with all your data.
    Learn More
  • 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: 3 This Week
    Last Update:
    See Project
  • 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
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB