Showing 2 open source projects for "machine"

View related business solutions
  • Build on Google Cloud with $300 in Free Credit Icon
    Build on Google Cloud with $300 in Free Credit

    New to Google Cloud? Get $300 in free credit to explore Compute Engine, BigQuery, Cloud Run, Vertex AI, and 150+ other products.

    Start your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query exabytes in BigQuery, or build AI apps with Vertex AI and Gemini. Once your credits are used, keep building with 20+ products with free monthly usage, including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. Sign up to start building right away.
    Start Free Trial
  • Enterprise-grade ITSM, for every business Icon
    Enterprise-grade ITSM, for every business

    Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity.

    Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
    Try it Free
  • 1
    erd

    erd

    Translates a plain text description of a relational database schema

    ...In case one wishes to have a statically linked erd as a result, this is possible to have by executing build-static_by-nix.sh: which requires the nix package manager to be installed on the building machine. NixOS itself is not a requirement.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2
    TensorFlow Haskell

    TensorFlow Haskell

    Haskell bindings for TensorFlow

    The tensorflow-haskell package provides Haskell-language bindings for TensorFlow, giving Haskell developers the ability to build and run computation graphs, machine learning models, and leverage TensorFlow's ecosystem—though it is not an official Google release. As an expedient we use docker for building. Once you have docker working, the following commands will compile and run the tests. Run the install_macos_dependencies.sh script in the tools/ directory. The script installs dependencies via Homebrew and then downloads and installs the TensorFlow library on your machine under /usr/local. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB