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# ConvNet [![experimental](http://badges.github.io/stability-badges/dist/experimental.svg)](http://github.com/badges/stability-badges) # | ||
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This is an example of a 3-layer ConvNet built with Gorgonia. It uses the MNIST data as an example. The MNIST data is not provided, and MUST be put in `../testdata`. | ||
This is an example of a 3-layer ConvNet built with Gorgonia. It uses the MNIST data as an example. The MNIST data is not provided, and MUST be put in `../testdata`. | ||
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This example currently works but is very slow, pending a change in transpose algorithms. | ||
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A step by step tutorial is exposed on to the Gorgonia website: [https://gorgonia.org/tutorials/mnist/](https://gorgonia.org/tutorials/mnist/) | ||
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# Disclaimer # | ||
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This example comes with a basic implementation of a ConvNet. It does not contain: | ||
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* Model serialization (you cannot save your models) | ||
* Checkpointing. | ||
* Multithreaded batching (training is highly serial). | ||
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This package contains primitives to read the mnist dataset as exposed on [Yann LeCun's website]( | ||
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It exposes a single `Load` method that creates tensors from the data sets. | ||
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Take a look at the [convnet](../convnet) directoy for a neural net implementation using the mnist dataset. | ||
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more info on the Gorgonia website: [https://gorgonia.org/tutorials/mnist/](https://gorgonia.org/tutorials/mnist/) |