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Course Outline
Foundations of Edge AI and Nano Banana
- Defining the key characteristics of edge-AI workloads
- Overview of Nano Banana’s architecture and core capabilities
- An analysis of edge versus cloud deployment strategies
Model Preparation for Edge Environments
- Model selection criteria and establishing baseline performance
- Reviewing dependencies and hardware compatibility
- Exporting models to prepare for optimization pipelines
Techniques for Model Compression
- Strategies for pruning and structural sparsity
- Reducing parameters through weight sharing
- Measuring the impact of compression on model performance
Optimizing for Edge via Quantization
- Methods for post-training quantization
- Workflows for quantization-aware training
- Exploring INT8, FP16, and mixed-precision strategies
Acceleration Using Nano Banana
- Leveraging Nano Banana’s hardware accelerators
- Integrating ONNX standards with specific hardware backends
- Benchmarking performance for accelerated inference
Deploying to Edge Devices
- Embedding models into mobile or embedded applications
- Configuring runtimes and setting up monitoring
- Resolving common deployment challenges
Performance Profiling and Strategic Trade-offs
- Managing constraints related to latency, throughput, and heat
- Balancing accuracy against performance metrics
- Developing iterative optimization approaches
Best Practices for Sustaining Edge-AI Systems
- Implementing version control and continuous updates
- Managing model rollbacks and ensuring compatibility
- Addressing security and system integrity concerns
Course Summary and Future Directions
Requirements
- A solid grasp of machine learning workflows
- Hands-on experience with Python-based model development
- Familiarity with various neural network architectures
Target Audience
- ML Engineers
- Data Scientists
- MLOps Practitioners
14 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
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