This is a repository created to explore different tools and technologies related to feature stores to build and serve ML models.
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Updated
Sep 7, 2022 - Python
This is a repository created to explore different tools and technologies related to feature stores to build and serve ML models.
[👩🏫] In this repository I'll show you how to use Azure Databricks for development and training machine learning models, and build a MLOps pipeline to serving them with CI/CD process.
Quality Aware Feature Store
An end-to-end ML project for tabular data.
A simple app to help you find relevant machine learning papers to read.
An example of using Redis + RedisAI for a microservice that predicts consumer loan probabilities using Redis as a feature and model store and RedisAI as an inference server.
StreamSQL is a feature store for machine learning.
Zero-Dependency Feature Store. Available for Python and other languages.
A demo pipeline of using Redis as an online feature store with Feast for orchestration and Ray for training and model serving
Feast Feature Store Tutorial
A lightweight feature store for Pandas, DuckDB, or your choice of backend.
This repository contains my code solution to DeepLearning.AIs Practical Data Science On AWS Cloud Specialization.
Metastore Python SDK. Feature store and data catalog for machine learning.
An alternative Vertex AI (AI Platform) Featurestore Online Serving Client.
Go SDK to interact with the Hopsworks API
shows how to backfill Energy Consumption feature in a Feature Store (Hopsworks) using an orchestration tool (Prefect).
Feast Client SDK for Node.js
Get started with our Solution Accelerator for Propensity Scoring to build effective propensity scoring pipelines that: Enable the persistence, discovery and sharing of features across various model training exercises Quickly generate models by leveraging industry best practices Track and analyze the various model iterations generated
A curated list of awesome open source and commercial feature store tools and platforms 🚀
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