Showing 2 open source projects for "software projects"

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
  • Easily Host LLMs and Web Apps on Cloud Run Icon
    Easily Host LLMs and Web Apps on Cloud Run

    Run everything from popular models with on-demand NVIDIA L4 GPUs to web apps without infrastructure management.

    Run frontend and backend services, batch jobs, host LLMs, and queue processing workloads without the need to manage infrastructure. Cloud Run gives you on-demand GPU access for hosting LLMs and running real-time AI—with 5-second cold starts and automatic scale-to-zero so you only pay for actual usage. New customers get $300 in free credit to start.
    Try Cloud Run Free
  • 1
    Mass-based dissimilarity

    Mass-based dissimilarity

    A data dependent dissimilarity measure based on mass estimation.

    ...The presentation video in KDD 2016 is published on https://youtu.be/eotD_-SuEoo . Since this software is licensed under the Gnu General Public license GPLv3, any derivative work must be licensed under the GPL as well. This software is free only for non-commercial use. For commercial projects, it is possible to obtain a commercial license through the Commercial Services of Federation University Australia. Please email the first author of the original paper tingkm@nju.edu.cn for any inquiries about this software.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB