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Course Outline
Introduction to CV/NLP Deployment with CANN for Government
- Overview of the AI model lifecycle from training to deployment
- Key performance considerations for real-time computer vision (CV) and natural language processing (NLP)
- Introduction to CANN SDK tools and their role in integrating models into government systems
Preparing CV and NLP Models
- Exporting models from PyTorch, TensorFlow, and MindSpore for use in government applications
- Managing model inputs and outputs for image and text tasks to ensure compliance with public sector standards
- Utilizing ATC to convert models to OM format for efficient deployment in government environments
Deploying Inference Pipelines with AscendCL
- Running CV/NLP inference using the AscendCL API to support government workflows
- Developing preprocessing pipelines, including image resizing, tokenization, and normalization for government data
- Implementing postprocessing techniques such as bounding boxes, classification scores, and text output generation for government use cases
Performance Optimization Techniques
- Profiling CV and NLP models using CANN tools to enhance performance in government systems
- Reducing latency through mixed-precision and batch tuning for efficient government operations
- Managing memory and compute resources for streaming tasks in a government context
Computer Vision Use Cases
- Case study: Object detection for smart surveillance to enhance public safety
- Case study: Visual quality inspection in manufacturing to ensure regulatory compliance
- Building live video analytics pipelines on Ascend 310 to support real-time government monitoring
NLP Use Cases
- Case study: Sentiment analysis and intent detection for improved public engagement
- Case study: Document classification and summarization to streamline information management in government agencies
- Real-time NLP integration with REST APIs and messaging systems to enhance communication within government operations
Summary and Next Steps
Requirements
- Familiarity with deep learning for computer vision or natural language processing (NLP)
- Experience with Python and AI frameworks such as TensorFlow, PyTorch, or MindSpore
- Basic understanding of model deployment or inference workflows for government applications
Audience
- Computer vision and NLP practitioners utilizing Huawei’s Ascend platform for government initiatives
- Data scientists and AI engineers developing real-time perception models for government use
- Developers integrating CANN pipelines in manufacturing, surveillance, or media analytics for government projects
14 Hours
Testimonials (1)
I genuinely enjoyed the hands-on approach.
