Course Outline
Introduction
- Kubeflow on AWS compared to on-premise and other public cloud providers
Overview of Kubeflow Features and Architecture
Activating an AWS Account
Preparing and Launching GPU-enabled AWS Instances
Setting up User Roles and Permissions
Preparing the Build Environment
Selecting a TensorFlow Model and Dataset
Packaging Code and Frameworks into a Docker Image
Setting up a Kubernetes Cluster Using EKS
Staging the Training and Validation Data
Configuring Kubeflow Pipelines
Launching a Training Job using Kubeflow in EKS
Visualizing the Training Job in Runtime
Cleaning up After the Job Completes
Troubleshooting
Summary and Conclusion
Requirements
- A solid understanding of machine learning concepts.
- Familiarity with cloud computing principles.
- A general grasp of containers (Docker) and orchestration (Kubernetes).
- Some prior experience with Python programming is beneficial.
- Experience working with a command-line interface.
Target Audience
- Data science engineers.
- DevOps engineers interested in deploying machine learning models.
- Infrastructure engineers interested in deploying machine learning models.
- Software engineers aiming to integrate and deploy machine learning features within their applications.
Testimonials (3)
I've find out new interesting things about Lambda and Serverless
Oleg Buldumac - PUBLIC COURSE
Course - AWS Lambda for Developers
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
Course - 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.
