jakesnell/prototypical-networks
Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
This code helps machine learning researchers and practitioners explore "few-shot learning" by implementing Prototypical Networks. It takes in small datasets (like Omniglot) where each class has only a few examples, and outputs a trained model capable of classifying new, unseen examples from those classes. This is for researchers working on novel machine learning approaches where data is scarce for many categories.
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Use this if you are a machine learning researcher or student investigating few-shot learning techniques and want a reference implementation of Prototypical Networks.
Not ideal if you need an out-of-the-box solution for a production application or require extensive hyperparameter tuning and model management features.
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Jan 28, 2021
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