👨‍🔧
The Ops Compendium
  • The Ops Compendium
  • Definitions
    • Ops Definition Comparisons
  • ML & DL Compendium
  • MLOps
    • MLOps Intro
    • MLOps Teams
    • MLOps Literature
    • MLOps Course
    • MLOps Patterns
    • ML Experiment Management
    • ML Model Monitoring & Alerts
    • MLOps Tools
    • MLOps Deployment
    • Feature Stores & Feature Pipelines
    • Model Formats
    • AI As Data
    • MLOps Interview Questions
    • ML Architecture
  • DataOps
    • SQL
    • Tools
    • Databases
    • Database Modeling
    • Data Analytics
    • Data Engineering
    • Data Pipelines
    • Data Strategy
    • Data Vision
    • Data Teams
    • Data Catalogs
    • Data Governance
    • Data Quality
    • Data Observability
    • Data Program Management
    • Data KPIs
    • Data Mesh
    • Data Contract
    • Data Product
    • Data Engineering Questions & Training
    • Data Patterns
    • Data Architecture
    • Data Platforms
    • Data Lineage
  • DevOps
    • DevOps Strategy
    • DevOps Tools
      • Tutorials
      • Continuous Integration
      • Docker
      • Kubernetes
      • Cloud Objects
      • Key Value DB
      • API Gateway
      • Infrastructure As code
      • Logs
      • ELK
      • SLO
    • DevOps Courses
  • DevSecOps
    • Definitions
    • Tools
    • Concepts
  • Architecture
    • Problems
    • Development Concepts
    • System Design
Powered by GitBook
On this page
  • General Patterns
  • Patterns in Practice

Was this helpful?

Edit on GitHub
  1. MLOps

MLOps Patterns

PreviousMLOps CourseNextML Experiment Management

Last updated 10 months ago

Was this helpful?

General Patterns

Patterns in Practice

Visenger

Iguazio

- CS 329S: Machine Learning Systems Design - the course goes in-depth about how ML systems are built, and how to debug, root cause, monitor, etc.

Metaflow, medium (high level review), (schema), , (amazing), (extra), (loading and storing data docs!)

HyperparameterHunter,

An MLOps End-to-End system, i.e., "", using MetaFlow, Snowflake, DBT, Prefect, Great Expectations, Weights & Biases, Sagemaker, Lambda

- Snowflake, DBT, S3, CometML, Reclist, SageMaker.

MLOps Roadmap
Google’s Practitioners Guide to MLOps: A framework for continuous delivery and automation of machine learning
State of MLOps
Easy mlops with pycaret and mlflow
Challenges and solutions by iguazio
Stanford CS329
1
2
3
**4
5
6
Hyperopt, mlflow, unit test, concept drifts, using python and kafka
You dont need a bigger boat
A simplistic E2E system
ML product lifecycle patterns
ML design patterns book repo
MLOPS Design Patterns
Awesome MLOps
TOC
Template