Skip to main contentLearn how to build full machine learning pipelines — from raw data to deployed model — using Edge Impulse. These tutorials walk you through every step of the process for your use case or domain: collecting data, designing an impulse, training a model, testing results, and deploying to real hardware.
🖼️ Image tutorials
Explore visual ML applications including image classification and object detection.
🎧 Audio tutorials
Build models that understand sound — from detecting specific keywords to recognizing environmental noises.
📈 Time-series tutorials
Learn how to use motion, sensor, and other temporal data to detect activity, monitor environments, and identify anomalies.
⚙️ Hardware-specific tutorials
Deploy real applications on supported embedded hardware platforms and development kits.
🚀 What you’ll learn
By completing these tutorials, you’ll learn how to:
- Collect and label data from devices and sensors
- Design and configure impulses tailored to your data type
- Train and evaluate models using Edge Impulse Studio
- Optimize models for real-time edge deployment
- Deploy and run models on actual embedded hardware
Whether you’re a beginner exploring your first model or an expert integrating with specific hardware, these guides will help you go from idea to deployment, end-to-end. 
