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Duration 14 hours
Course Outline
Introduction to TensorFlow Lite
- An overview of TensorFlow Lite’s architecture and structure
- Contrasting TensorFlow Lite with TensorFlow and other edge AI frameworks
- Examining the advantages and obstacles of employing TensorFlow Lite for Edge AI
- Analyzing case studies involving TensorFlow Lite in Edge AI contexts
Configuring the TensorFlow Lite Environment
- Installing TensorFlow Lite alongside its necessary dependencies
- Setting up the development workspace
- Familiarizing with TensorFlow Lite-specific tools and libraries
- Practical exercises focused on environment configuration
Creating AI Models with TensorFlow Lite
- Designing and training AI models suitable for edge deployment
- Translating TensorFlow models into the TensorFlow Lite format
- Tuning models to enhance performance and efficiency
- Practical exercises covering model creation and format conversion
Deploying TensorFlow Lite Models
- Rolling out models on diverse edge devices (such as smartphones and microcontrollers)
- Executing inference tasks on edge hardware
- Resolving common deployment challenges
- Practical exercises dedicated to model deployment
Optimization Tools and Methods
- Understanding quantization and its associated benefits
- Applying pruning and model compression strategies
- Leveraging TensorFlow Lite’s built-in optimization utilities
- Practical exercises focused on model optimization
Constructing Real-World Edge AI Applications
- Building practical Edge AI solutions using TensorFlow Lite
- Integrating TensorFlow Lite models with external systems and applications
- Reviewing case studies of successful Edge AI implementations
- A capstone project for developing a functional Edge AI application
Conclusion and Future Directions
Requirements
- A solid grasp of AI and machine learning principles
- Prior experience working with TensorFlow
- Fundamental programming proficiency (Python is preferred)
Target Audience
- Software Developers
- Data Scientists
- AI Practitioners
Testimonials (1)
That we can cover advance topic and work with real-life example
