How will you train the #machinelearning model if you have a very small amount of labelled data and the remaining data is unlabeled?
Today I came across an amazing technique to handle such cases i.e.
“Pseudo Labeling “
How does it work?
1. Train model on a batch of labelled data
2. Use the trained model to predict labels on a batch of unlabeled data
3. Use the predicted labels to calculate the loss on unlabeled data
4. Combine labelled loss with unlabeled loss and backpropagate(repeat).
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