Interactive Transfer Learning

• Try it out
• See the code

Transfer learning is the processing of using the outputs of one ML model as an input for a different model.

In this example, I’m using MobileNet image classification results. I’m using a smaller, older version with 256 labels. The data looks like

[
  { "label": "cat", "value": 0.5 },
  { "label": "dog", "value": 0 }
]

It surprised me how well it worked to reuse MobileNet for dimensionality reduction. I would’ve thought I would need to retrain a portion of the model.

Next steps:

• arbitrary chaining of models
• parallel processing chains
• retraining models