Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.
Use Keras if you need a deep learning library that:
Allows for easy and fast prototyping (through user friendliness, modularity, and extensibility).
Supports both convolutional networks and recurrent networks, as well as combinations of the two.
Runs seamlessly on CPU and GPU.
Read the documentation at: https://keras.io/
For a detailed overview of what makes Keras special, see: https://keras.io/why-use-keras/
Keras is compatible with Python 2.7-3.6 and is distributed under the MIT license.
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Release files for keras 2.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| Keras-2.3.1.tar.gz | 1.3 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| Keras-2.3.1-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 1.7 MB
Release files / Keras-2.3.1.tar.gz
| Download URL | Keras-2.3.1.tar.gz |
|---|---|
| Size | 1.3 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Uploaded via |
twine/1.15.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.36.0 CPython/3.7.4
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Release files / Keras-2.3.1-py2.py3-none-any.whl
| Download URL | Keras-2.3.1-py2.py3-none-any.whl |
|---|---|
| Size | 377.8 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.15.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.36.0 CPython/3.7.4
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Security for keras 2.3.1
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