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Course Outline
Foundations of Containerization for AI & ML
- Fundamental principles of containerization
- The suitability of containers for ML workloads
- Distinguishing between containers and virtual machines
Handling Docker Images and Containers
- Comprehending images, layers, and registries
- Overseeing containers for ML experimentation
- Leveraging the Docker CLI for efficiency
Encapsulating ML Environments
- Preparing ML codebases for containerization
- Overseeing Python environments and dependencies
- Integrating CUDA and GPU support
Crafting Dockerfiles for Machine Learning
- Organizing Dockerfiles for ML projects
- Best practices for performance and maintainability
- Utilizing multi-stage builds
Encapsulating ML Models and Pipelines
- Packaging trained models into containers
- Managing data and storage strategies
- Implementing reproducible end-to-end workflows
Executing Containerized ML Services
- Exposing API endpoints for model inference
- Scaling services using Docker Compose
- Monitoring runtime behavior
Security and Compliance Factors
- Ensuring secure container configurations
- Managing access and credentials
- Protecting confidential ML assets
Production Deployment
- Publishing images to container registries
- Implementing containers in on-premises or cloud configurations
- Versioning and updating production services
Conclusion and Future Directions
Requirements
- A solid grasp of machine learning workflows
- Proficiency in Python or comparable programming languages
- Competence in basic Linux command-line operations
Target Audience
- ML engineers focused on deploying models to production
- Data scientists seeking to manage reproducible experimental environments
- AI developers creating scalable, containerized applications
14 Hours
Testimonials (3)
How trainer deliver knowledge so effectively
Vu Thoai Le - Reply Polska sp. z o. o.
Course - Certified Kubernetes Administrator (CKA) - exam preparation
the trainer had a lot of knowledge and patience to share with us
Bogdan Olaru
Course - Introduction to Docker
The knowledge and exchanges with Augustin