Technologies / Architecture

TensorFlow Lite for microcontrollers

A one-day training course introducing the world of machine learning on edge devices using TensorFlow Lite. Participants will learn the process of implementing machine learning models on microcontrollers, optimizing models for limited resources, and integrating with embedded systems. The program includes hands-on workshops using real-world use cases.

Issues

TensorFlow Lite architecture
Optimization of ML models
Implementation on microcontrollers
Memory management
Signal processing
Edge computing
Image recognition
Anomaly detection
Debugging ML models
Performance measurements
Model updates
Integration with embedded systems

Benefits

The participant will gain a working knowledge of implementing machine learning models on microcontrollers
Will master techniques to optimize TensorFlow Lite models for resource-constrained devices
Will learn to integrate ML models into existing embedded systems
Will learn methods for testing and debugging ML applications on edge devices
Will develop the ability to effectively manage memory in the context of ML
Will gain practical experience in deploying models on real devices

Who is this training for?

Embedded systems programmers interested in ML

IoT engineers working with edge computing

Machine learning specialists

Embedded application developers

R&D engineers in the area of AI/ML

Smart systems designers

Prerequisites

Basic knowledge of machine learning
Experience in programming embedded systems
Knowledge of Python language
Basic knowledge about TensorFlow
Experience working with microcontrollers

Training program

Conversion of models
Optimization for embedded devices

Implementation on microcontrollers
Configuring the environment
Integration with embedded system

Performance optimization
Practical applications

Signal processing

Data classification
Testing and implementation
Verification of accuracy
Performance measurements

Model updates

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Frequently asked questions

What are the prerequisites for this training?

For TensorFlow Lite for microcontrollers we recommend: Basic knowledge of machine learning; Experience in programming embedded systems; Knowledge of Python language.

What is the format and duration of this training?

The training lasts 1 day and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: Embedded systems programmers interested in ML; IoT engineers working with edge computing; Machine learning specialists.