GV

GeezerVison

The World Wide Web, restored to 800 pixels of glory.

Home|About|Gaming cabinet|Archives|How it works|Starter sites

On this site

  • Sign in
  • ActionsCI/CD and automation
  • CodespacesCloud development environments
  • All Features
  • Documentation
  • Training
  • Certifications
  • Build with Copilot
  • Customize Copilot
  • Integrations
  • Trending repos
  • GitHub Sponsors
  • Developer articles
  • Enterprises

This view

  • Original page
  • New address

GeezerVison is showing github.com — GitHub - sachuin23/feast: Feature Store for Machine Learning

BranchesTags
Open more actions menu
 
 

Latest commit

 

History

1,508 Commits
1,508 Commits

Folders and files

NameName
Last commit message
Last commit date
.github
.github
 
 
.prow
.prow
 
 
docs
docs
 
 
examples
examples
 
 
infra
infra
 
 
protos
protos
 
 
sdk
sdk
 
 
.dockerignore
.dockerignore
 
 
.gitbook.yaml
.gitbook.yaml
 
 
.gitignore
.gitignore
 
 
.helmdocsignore
.helmdocsignore
 
 
.pre-commit-config.yaml
.pre-commit-config.yaml
 
 
.prow.yaml
.prow.yaml
 
 
CHANGELOG.md
CHANGELOG.md
 
 
LICENSE
LICENSE
 
 
Makefile
Makefile
 
 
OWNERS
OWNERS
 
 
README.md
README.md
 
 
go.mod
go.mod
 
 
go.sum
go.sum
 
 

Repository files navigation


unit-tests integration-tests linter Docs Latest License GitHub Release

Overview

Feast (Feature Store) is an operational data system for managing and serving machine learning features to models in production. Please see our documentation for more information about the project.

Getting Started with Docker Compose

Clone the latest stable version of the Feast repository and navigate to the infra/docker-compose sub-directory:

git clone https://github.com/feast-dev/feast.git
cd feast/infra/docker-compose
cp .env.sample .env

The .env file can optionally be configured based on your environment.

Bring up Feast:

docker-compose pull && docker-compose up -d

Please wait for the containers to start up. This could take a few minutes since the quickstart contains demo infastructure like Kafka and Jupyter.

Once the containers are all running, please connect to the provided Jupyter Notebook containing example notebooks to try out.

Important resources

Please refer to the official documentation at https://docs.feast.dev

  • Concepts
  • Installation
  • Examples
  • Roadmap
  • Change Log
  • Slack (#Feast)

Notice

Feast is a community project and is still under active development. Your feedback and contributions are important to us. Please have a look at our contributing guide for details.

Contributors ✨

Thanks goes to these incredible people:

About

Feature Store for Machine Learning

feast.dev

Resources

Readme
Apache-2.0 license
Activity

Stars

0 stars

Watchers

0 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages

You are visitor 01402503 — GeezerVison does not store the pages you look up.
Best viewed with Netscape Navigator 4.7 or Internet Explorer 6 at 800×600. No cookies required.