Learning Resources
Comprehensive collection of resources to continue your MLOps journey beyond this workshop. From official documentation to community forums, these resources will help you master MLOps practices.
📚 Additional Resources
Documentation
- Kubeflow Documentation
Official Kubeflow documentation and guides
- KServe Documentation
Model serving platform documentation
- Argo Workflows Documentation
Kubernetes-native workflow engine docs
- Prometheus Documentation
Monitoring and alerting toolkit
- Grafana Documentation
Observability and visualization platform
Learning Materials
- MLOps Community
Community-driven MLOps resources and discussions
- MLOps on GCP Examples
Real-world MLOps implementations on Google Cloud
- Kubeflow Examples
Sample pipelines and workflows for Kubeflow
- MLOps Course (Coursera)
Comprehensive online course on MLOps practices
- MLOps Best Practices
Core principles and best practices for MLOps
Tools and Platforms
- MLflow - Model Management
Open source platform for managing ML lifecycle
- Weights & Biases - Experiment Tracking
Experiment tracking and model management
- DAGsHub - Data Science Platform
Git-based data science collaboration platform
- Feast - Feature Store
Open source feature store for ML
- Kedro - Data Pipeline Framework
Python framework for reproducible data science
Community
- Kubeflow Discussion Forum
Official Kubeflow community discussions
- Kubernetes Slack
Kubernetes community Slack workspace
- MLOps Community Slack
MLOps practitioners community
- CNCF Slack
Cloud Native Computing Foundation community
- Reddit r/MachineLearning
Machine learning discussions and resources
Books and Articles
- Designing Machine Learning Systems
Comprehensive guide to ML system design
- Building Machine Learning Pipelines
Hands-on guide to ML pipeline development
- MLOps: Continuous delivery and automation pipelines
Google Cloud MLOps architecture guide
- The MLOps Stack
Overview of MLOps technology stack
Certifications
- Google Cloud Professional ML Engineer
Google Cloud ML engineering certification
- AWS Machine Learning Specialty
AWS ML specialty certification
- Microsoft Azure AI Engineer Associate
Azure AI engineering certification
- CNCF Kubernetes Certifications
Kubernetes and cloud native certifications