문의를 보내주셔서 감사합니다! 팀원이 곧 연락드리겠습니다.
예약을 보내주셔서 감사합니다! 저희 팀 멤버 중 한 분이 곧 연락드리겠습니다.
코스 개요
Foundations of MLOps on Kubernetes
- Core concepts of MLOps
- MLOps vs traditional DevOps
- Key challenges of ML lifecycle management
Containerizing ML Workloads
- Packaging models and training code
- Optimizing container images for ML
- Managing dependencies and reproducibility
CI/CD for Machine Learning
- Structuring ML repositories for automation
- Integrating testing and validation steps
- Triggering pipelines for retraining and updates
GitOps for Model Deployment
- GitOps principles and workflows
- Using Argo CD for model deployment
- Version control of models and configurations
Pipeline Orchestration on Kubernetes
- Building pipelines with Tekton
- Managing multi-step ML workflows
- Scheduling and resource management
Monitoring, Logging, and Rollback Strategies
- Tracking data drift and model performance
- Integrating alerting and observability
- Rollback and failover approaches
Automated Retraining and Continuous Improvement
- Designing feedback loops
- Automating scheduled retraining
- Integrating MLflow for tracking and experiment management
Advanced MLOps Architectures
- Multi-cluster and hybrid-cloud deployment models
- Scaling teams with shared infrastructure
- Security and compliance considerations
Summary and Next Steps
요건
- An understanding of Kubernetes fundamentals
- Experience with machine learning workflows
- Knowledge of Git-based development
Audience
- ML engineers
- DevOps engineers
- ML platform teams
14 시간
회원 평가 (3)
그는 인내심이 있었고 우리가 뒤쳐진다는 것을 이해했습니다.
Albertina - REGNOLOGY ROMANIA S.R.L.
코스 - Deploying Kubernetes Applications with Helm
기계 번역됨
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
코스 - MLflow
I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.
