awesome-kubernetes/docs/mlops.md

Machine Learning Ops (MLOps)

• Introduction
• Kubeflow
• Tweets

Introduction

• 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
• cloudblogs.microsoft.com: Simple steps to create scalable processes to deploy ML models as microservices
• ML Platform Workshop Example code for a basic ML Platform based on Pulumi, FastAPI, DVC, MLFlow and more
• rubrix A free and open-source tool to explore, label, and monitor data for NLP projects.
• towardsdatascience.com: Automatically Generate Machine Learning Code with Just a Few Clicks Using Traingenerator to easily create PyTorch and scikit-learn template codes for machine learning model training
• towardsdatascience.com: Schemafull streaming data processing in ML pipelines Making containerized Python streaming data pipelines leverage schemas for data validation using Kafka with AVRO and Schema Registry
• analyticsindiamag.com: Top tools for enabling CI/CD in ML pipelines

Kubeflow

• kubeflow The Machine Learning Toolkit for Kubernetes
• medium.com: Machine Learning using Kubeflow
• infracloud.io: Machine Learning Orchestration on Kubernetes using Kubeflow

Tweets

Click to expand!

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

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You don't need to go to a university to learn machine learning - you can do it from your living room, for completely free.

Here is an extensive list of curated free courses and tutorials, from beginner to advanced. ↓

(Trust me, you want to bookmark this tweet.)

— Tivadar Danka (@TivadarDanka) September 21, 2021

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I started taking data science courses last year, after studying and coding for at least 10 hours 6 days a week and doing several ML projects alongside data analysis projects, I finally got my first data analyst offer from a Nigerian bank last week after countless rejections

— Sam (@SamsonTontoye) February 20, 2022

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