AI Inference and Deployment with CloudMatrix Training Course
CloudMatrix serves as Huawei's consolidated AI development and deployment platform, engineered to facilitate scalable, production-ready inference pipelines.
This instructor-led live training, available either online or onsite, targets beginner to intermediate-level AI professionals looking to deploy and monitor AI models using the CloudMatrix platform, integrated with CANN and MindSpore.
Upon completing this training, participants will be capable of:
- Utilizing CloudMatrix for model packaging, deployment, and serving.
- Converting and optimizing models for Ascend chipsets.
- Establishing pipelines for both real-time and batch inference tasks.
- Monitoring deployments and fine-tuning performance within production environments.
Course Format
- Interactive lectures and discussions.
- Practical application of CloudMatrix through real-world deployment scenarios.
- Guided exercises concentrating on conversion, optimization, and scaling.
Customization Options
- To request tailored training for this course based on your specific AI infrastructure or cloud environment, please reach out to us to arrange.
Course Outline
Introduction to Huawei CloudMatrix
- Overview of the CloudMatrix ecosystem and deployment flow.
- Supported models, formats, and deployment modes.
- Typical use cases and compatible chipsets.
Preparing Models for Deployment
- Exporting models from training tools (MindSpore, TensorFlow, PyTorch).
- Utilizing ATC (Ascend Tensor Compiler) for format conversion.
- Understanding static versus dynamic shape models.
Deploying to CloudMatrix
- Creating services and registering models.
- Deploying inference services via the UI or CLI.
- Managing routing, authentication, and access control.
Serving Inference Requests
- Comparing batch versus real-time inference flows.
- Designing data preprocessing and postprocessing pipelines.
- Integrating CloudMatrix services with external applications.
Monitoring and Performance Tuning
- Accessing deployment logs and tracking requests.
- Implementing resource scaling and load balancing.
- Optimizing latency and throughput.
Integration with Enterprise Tools
- Connecting CloudMatrix with OBS and ModelArts.
- Leveraging workflows and model versioning.
- Applying CI/CD practices for model deployment and rollback.
End-to-End Inference Pipeline
- Deploying a complete image classification pipeline.
- Conducting benchmarks and validating accuracy.
- Simulating failover scenarios and system alerts.
Summary and Next Steps
Requirements
- Understanding of AI model training workflows.
- Experience with Python-based machine learning frameworks.
- Basic familiarity with cloud deployment concepts.
Audience
- AI operations teams.
- Machine learning engineers.
- Cloud deployment specialists working with Huawei infrastructure.
Need help picking the right course?
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AI Inference and Deployment with CloudMatrix Training Course - Enquiry
AI Inference and Deployment with CloudMatrix - Consultancy Enquiry
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.
Ireneusz - Inter Cars S.A.
Course - Intelligent Applications Fundamentals
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