Showing 2 open source projects for "prototype"

View related business solutions
  • Ship Agents Faster Icon
    Ship Agents Faster

    Transform your applications and workflows into powerful agentic systems at global scale.

    Gemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
    Start Free
  • Custom VMs From 1 to 96 vCPUs With 99.95% Uptime Icon
    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

    General-purpose, compute-optimized, or GPU/TPU-accelerated. Built to your exact specs.

    Live migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
    Start Free
  • 1
    Query.jl

    Query.jl

    Query almost anything in julia

    ...One can for example query any of the following data sources: any array, DataFrames, DataStreams (including CSV, Feather, SQLite, ODBC), DataTables, IndexedTables, TimeSeries, Temporal, TypedTables and DifferentialEquations (any DESolution). The package currently provides working implementations for in-memory data sources, but will eventually be able to translate queries into e.g. SQL. There is a prototype implementation of such a "query provider" for SQLite in the package, but it is experimental at this point and only works for a very small subset of queries. Query is heavily inspired by LINQ, in fact right now the package is largely an implementation of the LINQ part of the C# specification. Future versions of Query will most likely add features that are not found in the original LINQ design.
    Downloads: 8 This Week
    Last Update:
    See Project
  • 2
    Bayesian Julia

    Bayesian Julia

    Bayesian Statistics using Julia and Turing

    Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from...
    Downloads: 6 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next