[👩🏫] 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.
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Updated
Apr 26, 2024 - Jupyter Notebook
[👩🏫] 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.
Feast as a combinator.ml component
Feast Feature Store Tutorial
A lightweight feature store for Pandas, DuckDB, or your choice of backend.
Zero-Dependency Feature Store. Available for Python and other languages.
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).
This repository contains my code solution to DeepLearning.AIs Practical Data Science On AWS Cloud Specialization.
This is a learning repository about Databricks and Recommendation Systems
This is a repository created to explore different tools and technologies related to feature stores to build and serve ML models.
End-to-end ML project for tabular data.
StreamSQL is a feature store for machine learning.
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
Feast Client SDK for Node.js
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.
A curated list of awesome open source and commercial feature store tools and platforms 🚀
Quality Aware Feature Store
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