Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow.
It was developed with a focus on enabling fast experimentation and providing a delightful developer experience. The purpose of Keras is to give an unfair advantage to any developer looking to ship ML-powered apps.
Keras is:
Simple – but not simplistic. Keras reduces developer cognitive load to free you to focus on the parts of the problem that really matter. Keras focuses on ease of use, debugging speed, code elegance & conciseness, maintainability, and deployability (via TFServing, TFLite, TF.js).
Flexible – Keras adopts the principle of progressive disclosure of complexity: simple workflows should be quick and easy, while arbitrarily advanced workflows should be possible via a clear path that builds upon what you’ve already learned.
Powerful – Keras provides industry-strength performance and scalability: it is used by organizations and companies including NASA, YouTube, and Waymo. That’s right – your YouTube recommendations are powered by Keras, and so is the world’s most advanced driverless vehicle.
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Release files for keras 2.14.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| keras-2.14.0.tar.gz | 1.3 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| keras-2.14.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.0 MB
Release files / keras-2.14.0.tar.gz
| Download URL | keras-2.14.0.tar.gz |
|---|---|
| Size | 1.3 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/4.0.2 CPython/3.8.10
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Release files / keras-2.14.0-py3-none-any.whl
| Download URL | keras-2.14.0-py3-none-any.whl |
|---|---|
| Size | 1.7 MB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.10
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