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Duration 21 hours
Course Outline
Overview of Huawei CloudMatrix
- The CloudMatrix ecosystem and its deployment workflow.
- Compatible models, data formats, and deployment modes.
- Common application cases and supported chipset architectures.
Model Preparation for Deployment
- Exporting models from training frameworks such as MindSpore, TensorFlow, and PyTorch.
- Utilizing ATC (Ascend Tensor Compiler) for efficient format conversion.
- Distinguishing between static and dynamic shape models.
Deployment on CloudMatrix
- Creating services and registering models.
- Launching inference services through the UI or CLI.
- Configuring routing, authentication, and access control policies.
Handling Inference Requests
- Comparing batch versus real-time inference processes.
- Implementing data preprocessing and postprocessing pipelines.
- Integrating CloudMatrix services into external applications.
Monitoring & Performance Optimization
- Analyzing deployment logs and tracking request patterns.
- Managing resource scaling and load balancing.
- Refining latency and optimizing throughput.
Enterprise Tool Integration
- Connecting CloudMatrix with OBS and ModelArts.
- Implementing workflows and model version control.
- Establishing CI/CD practices for model deployment and rollback.
Complete Inference Pipeline
- Deploying a full image classification workflow.
- Conducting benchmarks and validating accuracy.
- Simulating failover scenarios and system alert responses.
Recap & Future Directions
Requirements
- A solid grasp of AI model training workflows.
- Proficiency with Python-based machine learning frameworks.
- Foundational knowledge of cloud deployment principles.
Target Audience
- AI operations (MLOps) teams.
- Machine learning engineers.
- Cloud deployment specialists utilizing Huawei infrastructure.
Testimonials (2)
The extensive selection of tools presented
Miruna Buzduga - Aeronamic Eastern Europe
Course - AI Enablement Training for Engineers
Step by step training with a lot of exercises. It was like a workshop and I am very glad about that.
