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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Keras package for deep residual networks
| Date | Stars |
|---|---|
| 2026-07-24 | 302 |
| 2026-07-25 | 302 |
| 2026-07-28 | 302 |
| 2026-07-30 | 302 |
| 2026-08-06 | 302 |
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Momentum
0.0
growth rate 0.00%/day
Keras-ResNet
============
.. image:: https://travis-ci.org/broadinstitute/keras-resnet.svg?branch=master
:target: https://travis-ci.org/broadinstitute/keras-resnet
Keras-ResNet is **the** Keras package for deep residual networks. It's fast *and* flexible.
A tantalizing preview of Keras-ResNet simplicity:
.. code-block:: python
>>> import keras
>>> import keras_resnet.models
>>> shape, classes = (32, 32, 3), 10
>>> x = keras.layers.Input(shape)
>>> model = keras_resnet.models.ResNet50(x, classes=classes)
>>> model.compile("adam", "categorical_crossentropy", ["accuracy"])
>>> (training_x, training_y), (_, _) = keras.datasets.cifar10.load_data()
>>> training_y = keras.utils.np_utils.to_categorical(training_y)
>>> model.fit(training_x, training_y)
Installation
------------
Installation couldn’t be easier:
.. code-block:: bash
$ pip install keras-resnet
Contributing
------------
#. Check for open issues or open a fresh issue to start a discussion around a feature idea or a bug. There is a `Contributor Friendly`_ tag for issues that should be ideal for people who are not very familiar with the codebase yet.
#. Fork `the repository`_ on GitHub to start making your changes to the **master** branch (or branch off of it).
#. Write a test which shows that the bug was fixed or that the feature works as expected.
#. Send a pull request and bug the maintainer until it gets merged and published. :) Make sure to add yourself to AUTHORS_.
.. _`the repository`: http://github.com/0x00b1/keras-resnet
.. _AUTHORS: https://github.com/0x00b1/keras-resnet/blob/master/AUTHORS.rst
.. _Contributor Friendly: https://github.com/0x00b1/keras-resnet/issues?direction=desc&labels=Contributor+Friendly&page=1&sort=updated&state=open
Excerpt of 1,794 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:5d0280a29d486838, topic:deep-learning, topic:tensorflow