Maml
Visit ToolMaml is an Open Source & Models tool that provides code for Model-Agnostic Meta-Learning. It facilitates fast adaptation of deep networks for few-shot supervised learning experiments.
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Maml is an Open Source & Models tool that provides code for Model-Agnostic Meta-Learning. It facilitates fast adaptation of deep networks for few-shot supervised learning experiments.
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About
Maml is an open-source code repository for Model-Agnostic Meta-Learning (MAML), a technique designed for the fast adaptation of deep networks. Developed by cbfinn, this repository provides the foundational code accompanying the paper "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks" (Finn et al., ICML 2017). It specifically includes implementations for few-shot supervised learning domain experiments, covering tasks such as sinusoid regression, Omniglot classification, and MiniImagenet classification. The project is built using Python 2.* or 3.* and TensorFlow v1.0+, making it accessible for researchers and developers working in meta-learning and few-shot learning. Users can access data preparation instructions for Omniglot and MiniImagenet, and detailed usage instructions are available within the `main.py` file.
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