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Course Outline
Introduction to TensorFlow Lite
- An overview of TensorFlow Lite and its architectural design.
- Comparative analysis between TensorFlow Lite and other edge AI frameworks.
- Advantages and challenges associated with using TensorFlow Lite for Edge AI.
- Case studies illustrating TensorFlow Lite applications in Edge AI.
Establishing the TensorFlow Lite Environment
- Installation of TensorFlow Lite and its required dependencies.
- Configuration of the development workspace.
- Introduction to essential TensorFlow Lite tools and libraries.
- Practical exercises focused on environment setup.
Creating AI Models with TensorFlow Lite
- Designing and training AI models intended for edge deployment.
- Converting existing TensorFlow models into the TensorFlow Lite format.
- Optimizing models for enhanced performance and efficiency.
- Practical exercises covering model development and conversion.
Deploying TensorFlow Lite Models
- Implementing models on various edge devices (e.g., smartphones, microcontrollers).
- Executing inferences directly on edge devices.
- Diagnosing and resolving deployment challenges.
- Practical exercises for model deployment.
Tools and Techniques for Model Optimization
- Understanding quantization and its advantages.
- Pruning and methods for model compression.
- Leveraging optimization tools provided by TensorFlow Lite.
- Practical exercises focused on model optimization.
Constructing Practical Edge AI Applications
- Developing real-world Edge AI applications using TensorFlow Lite.
- Integrating TensorFlow Lite models with other systems and applications.
- Case studies highlighting successful Edge AI projects.
- A hands-on project to build a functional Edge AI application.
Summary and Next Steps
Requirements
- A foundational understanding of AI and machine learning concepts.
- Prior experience working with TensorFlow.
- Basic programming proficiency (Python is recommended).
Target Audience
- Developers
- Data scientists
- AI practitioners
14 Hours
Testimonials (1)
That we can cover advance topic and work with real-life example
