Machine Learning Ops (MLOps)¶
- cd.foundation: Announcing the CD Foundation MLOps SIG
- dafriedman97.github.io: Machine Learning from Scratch Derivations in Concept and Code.
- cortex.dev: How to build a pipeline to retrain and deploy models
- github: A very Long never ending Learning around Data Engineering & Machine Learning
- towardsdatascience.com: A Kubernetes architecture for machine learning web-application deployments Use Kubernetes to reduce machine learning infrastructure costs and scale resources with ease.
- cloud.google.com: How to use a machine learning model from a Google Sheet using BigQuery ML
- itnext.io: Building ML Componentes on Kubernetes
- towardsdatascience.com: Deploying An ML Model With FastAPI — A Succinct Guide
- analyticsvidhya.com: Bring DevOps To Data Science With MLOps
- redhat.com: Introducing Red Hat OpenShift Data Science
- towardsdatascience.com: Production Machine Learning Monitoring: Outliers, Drift, Explainers & Statistical Performance A practical deep dive on production monitoring architectures for machine learning at scale using real-time metrics, outlier detectors, drift detectors, metrics servers and explainers.
- towardsdatascience.com: From DevOps to MLOPS: Integrate Machine Learning Models using Jenkins and Docker How to automate data science code with Jenkins and Docker: MLOps = ML + DEV + OPS
- kubeflow The Machine Learning Toolkit for Kubernetes
- medium.com: Machine Learning using Kubeflow
- infracloud.io: Machine Learning Orchestration on Kubernetes using Kubeflow
To my JVM friends looking to explore Machine Learning techniques - you don’t necessarily have to learn Python to do that. There are libraries you can use from the comfort of your JVM environment. 🧵👇— Maria Khalusova (@mariaKhalusova) November 26, 2020