featureform
feathr
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| featureform | feathr | |
|---|---|---|
| 28 | 9 | |
| 1,674 | 1,929 | |
| 1.1% | 1.2% | |
| 9.7 | 6.7 | |
| 8 days ago | 21 days ago | |
| Jupyter Notebook | Scala | |
| Mozilla Public License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
featureform
- Still look familiar?
- Featureform: A Python Framework for the Entire Feature Lifecycle. Define, Version, Orchestrate, & Deploy ML Features with OSS Featureform!
- Does this look familiar?
- Does this look familiar? Define, Manage, & Serve your ML Features with OSS Featureform!
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What’s your process for deploying a data pipeline from a notebook, running it, and managing it in production?
Feature store: new hot one: https://www.featureform.com/
- featureform / featureform :
- Featureform: An Open-Source Feature Store for your ML Features
feathr
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[D] good feature store?
For open source/free feature stores, look into Feathr https://github.com/feathr-ai/feathr and Feast https://feast.dev/.
- Open sourcing Feathr – LinkedIn’s feature store for productive machine learning
- Show HN: Feathr – An Open-Source, Enterprise-Grade Virtual Feature Store
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[P] Feathr - An Open-Source, Enterprise-Grade and High-Performance Feature Store
Open Sourcing Feathr
- [D] Your 🫵 Preferred Feature Stores?
- Feathr – LinkedIn Open Sourced Its Feature Store
- Feathr – an enterprise-grade, high performance feature store
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LinkedIn Open-Sources ‘Feathr’, It’s Feature Store To Simplify Machine Learning (ML) Feature Management And Improve Developer Productivity
LinkedIn research team has recently open-sourced feature store, Feathr, created to simplify machine learning (ML) feature management and increase developer productivity. Feathr is used by dozens of LinkedIn applications to define features, compute them for training, deploy them in production, and share them across consumers. Compared to previous application-specific feature pipeline solutions, Feathr users reported significantly reduced time required to add new features to model training and improved runtime performance.
What are some alternatives?
feast - Feature Store for Machine Learning
hopsworks - Hopsworks - Data-Intensive AI platform with a Feature Store
Milvus - A cloud-native vector database, storage for next generation AI applications
awesome-vector-search - Collections of vector search related libraries, service and research papers
OpenMLDB - OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
metarank - A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
Clustering4Ever - C4E, a JVM friendly library written in Scala for both local and distributed (Spark) Clustering.
vald - Vald. A Highly Scalable Distributed Vector Search Engine
CIlib - Typesafe, purely functional Computational Intelligence