Showing 2 open source projects for "research"

View related business solutions
  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New to Google Cloud? Get $300 in credits to explore Compute Engine, BigQuery, Cloud Run, Gemini Enterprise Agent Platform, and more.

    Start your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
    Claim $300 Free
  • Train ML Models With SQL You Already Know Icon
    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

    Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
    Try Free
  • 1
    PyTorch Lightning

    PyTorch Lightning

    The lightweight PyTorch wrapper for high-performance AI research

    Scale your models, not your boilerplate with PyTorch Lightning! PyTorch Lightning is the ultimate PyTorch research framework that allows you to focus on the research while it takes care of everything else. It's designed to decouple the science from the engineering in your PyTorch code, simplifying complex network coding and giving you maximum flexibility. PyTorch Lightning can be used for just about any type of research, and was built for the fast inference needed in AI research and production. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    Kodus

    Kodus

    AI code reviews, just like your senior dev would do

    ...It provides a structured set of tools and abstractions that help teams design agent behaviors, orchestrate data pipelines, optimize inference, and integrate AI capabilities with applications or services. The platform often includes model management, scalable training workflows, and orchestration patterns that help teams move from research or prototypes to production-ready AI deployments. Through configurable pipelines and a focus on modularity, it supports experimentation while maintaining reproducibility and performance. Its tooling is typically designed to handle real-world imperatives like logging, monitoring, versioning, and hooking into operational infrastructure.
    Downloads: 6 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
Auth0 Logo