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Course Outline
Introduction to TensorFlow Lite
- Overview of TensorFlow Lite and its architecture, designed specifically to support efficient execution on edge devices.
- Comparison with TensorFlow and other edge AI frameworks, highlighting the unique advantages and capabilities of TensorFlow Lite for government applications.
- Benefits and challenges of using TensorFlow Lite for Edge AI in public sector projects.
- Case studies of TensorFlow Lite in Edge AI applications, demonstrating its effectiveness and versatility for government use.
Setting Up the TensorFlow Lite Environment
- Installing TensorFlow Lite and its dependencies to ensure a robust development setup.
- Configuring the development environment to meet the specific needs of edge AI projects for government.
- Introduction to TensorFlow Lite tools and libraries, essential for efficient model development and deployment.
- Hands-on exercises for setting up the TensorFlow Lite environment, ensuring participants are well-prepared for practical applications.
Developing AI Models with TensorFlow Lite
- Designing and training AI models tailored for edge deployment in government contexts.
- Converting TensorFlow models to the TensorFlow Lite format, optimizing them for resource-constrained devices.
- Optimizing models for performance and efficiency to meet the stringent requirements of public sector projects.
- Hands-on exercises for model development and conversion, providing practical experience in creating efficient edge AI solutions.
Deploying TensorFlow Lite Models
- Deploying models on various edge devices, such as smartphones and microcontrollers, to support diverse government applications.
- Running inferences on edge devices to enable real-time decision-making and data processing for government operations.
- Troubleshooting deployment issues to ensure smooth integration and reliability of TensorFlow Lite models for government use.
- Hands-on exercises for model deployment, allowing participants to gain hands-on experience in deploying AI solutions in real-world scenarios.
Tools and Techniques for Model Optimization
- Quantization and its benefits in reducing model size and improving inference speed for government applications.
- Pruning and model compression techniques to enhance the efficiency of AI models deployed on edge devices.
- Utilizing TensorFlow Lite's optimization tools to achieve optimal performance and resource utilization for government projects.
- Hands-on exercises for model optimization, providing practical skills in enhancing the performance of AI models for government use.
Building Practical Edge AI Applications
- Developing real-world Edge AI applications using TensorFlow Lite, tailored to address specific challenges and opportunities in the public sector.
- Integrating TensorFlow Lite models with other systems and applications to create comprehensive solutions for government operations.
- Case studies of successful Edge AI projects that demonstrate the impact and effectiveness of TensorFlow Lite for government initiatives.
- Hands-on project for building a practical Edge AI application, giving participants the opportunity to apply their knowledge in a real-world context for government use.
Summary and Next Steps
Requirements
- A comprehensive understanding of artificial intelligence and machine learning principles for government applications
- Practical experience with TensorFlow for government projects
- Fundamental programming skills, with a recommendation for Python, to support efficient development for government tasks
Audience
- Developers working on government initiatives
- Data scientists supporting public sector projects
- AI practitioners focused on governmental applications
14 Hours
