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Learning blocks

After extracting meaningful features from the raw signal using signal processing, you can now train your model using a learning block. We provide a number of pre-defined learning blocks:
​Classification (Keras).
​Regression (Keras).
​Anomaly Detection (K-means).
​Anomaly Detection (GMM).
​Image Classification (using Transfer Learning).
​Keyword Spotting (using Transfer Learning).
​Object Detection (using MobileNetV2 SSD FPN).
​Object Detection (using FOMO).
Miss an architecture? You can create a custom learning block, with PyTorch, Keras or scikit-learn.
For most of the learning blocks (except K-means Anomaly Detection), you can use the Switch to expert mode button to access the full Keras API for custom architectures, rebalancing your weights, and more.

Feature explorer

Classification (Keras)

Last modified 2mo ago