ML & data engineering

In this ML & data engineering section, you will discover useful techniques to train your models, generate synthetic datasets, or to perform advanced feature extraction:

Edge Impulse Python SDK

• Using the Edge Impulse Python SDK to run EON Tuner

• Using the Edge Impulse Python SDK to upload and download data

• Using the Edge Impulse Python SDK with Hugging Face

• Using the Edge Impulse Python SDK with SageMaker Studio

• Using the Edge Impulse Python SDK with TensorFlow and Keras

• Using the Edge Impulse Python SDK with Weights & Biases

Synthetic data

Learn about synthetic data and how to integrate synthetic data models into your Edge Impulse project with the following guides:

• Synthetic data overview

• Synthetic data integration

The following tutorials detail how to work with synthetic datasets in Edge Impulse:

• Generate audio with Eleven Labs Sound Effects model datasets

• Generate image datasets using Dall·E

• Generate keyword-spotting datasets

• Generate physics simulation datasets

See also:

• Generate synthetic datasets using custom transformation blocks

• Generate synthetic datasets using NVIDIA Omniverse

Other

• Classification with multiple 2D inputs

• FOMO self-attention

• Label audio data using your existing models

• Label image data using GPT-4o