Training: TensorFlow Lite
Level
AdvancedDuration
16h / 2 daysDate
Individually arrangedPrice
Individually arrangedTraining: TensorFlow Lite
The TensorFlow Lite training is an intensive two-day course focused on the practical application of TensorFlow Lite for deploying AI models on mobile and embedded devices. The program is designed so that 80% of the time is dedicated to hands-on workshops and 20% to theory. Participants will learn how to optimize ML models, deploy them on mobile devices, and monitor their performance in real-world applications.
What will you learn?
- How to configure and manage TensorFlow Lite for deploying ML models on mobile devices
- How to convert and optimize TensorFlow models into the TensorFlow Lite format
- How to deploy and monitor TensorFlow Lite models on Android and iOS
- How to integrate TensorFlow Lite with mobile applications and cloud services
Required technical skills
- Basic knowledge of Python programming
- Basic knowledge of machine learning
- Experience in developing mobile applications for Android or iOS
Who is this training for?
Mobile application developers who want to integrate AI models into their apps-
Data scientists and ML engineers who want to deploy and optimize models on mobile devices
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IT specialists who want to use TensorFlow Lite for deploying AI models in resource-constrained environments
Training Program
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Day 1: Introduction to TensorFlow Lite and Model Optimization
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Basics of TensorFlow Lite
- Introduction to TensorFlow Lite and its architecture
- Installation and configuration of TensorFlow Lite on different platforms
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Preparing and optimizing models
- Converting TensorFlow models to TensorFlow Lite format
- Optimizing models using quantization, pruning, and other techniques
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Workshop: Model conversion and optimization
- Practical exercises with conversion and optimization on a real ML model
- Analyzing optimization results
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Introduction to mobile implementation
- Overview of TensorFlow Lite libraries for Android and iOS
- Integrating TensorFlow Lite into mobile applications
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Day 2: Advanced Techniques and Practical Applications
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Implementing models on mobile devices
- Practical aspects of deploying TensorFlow Lite models on Android and iOS
- Handling model inputs and outputs in mobile apps
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Monitoring and debugging TensorFlow Lite models
- Techniques for monitoring model performance on mobile devices
- Debugging and optimizing deployed models
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Workshop: Model deployment and testing
- Practical exercises with deploying a model on a mobile device
- Testing the model in a real mobile application
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Integration with tools and cloud services
- Integrating TensorFlow Lite with Google Cloud AI services
- Using CI/CD tools to automate model deployments
Contact us
we will organize training for you tailored to your needs
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