A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
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Updated
Aug 19, 2024
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
A curated collection of publicly available resources on how technology and tech-savvy organizations around the world practice Site Reliability Engineering (SRE)
A curated list of articles that cover the software engineering best practices for building machine learning applications.
An open-source ML pipeline development platform
Fire up your models with the flame 🔥
A Collection of GitHub Actions That Facilitate MLOps
Azure Databricks MLOps sample for Python based source code using MLflow without using MLflow Project.
The DBT of ML, as Aligned describes data dependencies in ML systems, and reduce technical data debt
A pipeline to CI/CD of a machine learning model on Google Cloud Run
Efficient streaming data ingestion, transformation & activation
Find the samples, in the test data, on which your (generative) model makes mistakes.
Designing IT and ML Applications using Systems Thinking Approach at IIT Bhilai (CS559)
Serving large ml models independently and asynchronously via message queue and kv-storage for communication with other services [EXPERIMENT]
Dicoding Submission MLOps Heart Failure Detection using ML Pipeline, Heroku Deployment and Prometheus Monitoring
Vehicle data classification (supervised, unsupervised learning)
A ready to use architecture for processing data and performing machine learning in Azure
A prefect extension that builds on top of the task decorator to reduce negative engineering!
Repo for running Whylogs as part of a CI workflow using github actions.
The universal data connector
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