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Keras 3 is a multi-backend deep learning framework, with support for JAX, TensorFlow, and PyTorch. Effortlessly build and train models for computer vision.
Keras resources. This is a directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library.
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fchollet has 16 repositories available. Follow their code on GitHub.
Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs.
This repository contains code for the following Keras models. All architectures are compatible with both TensorFlow and Theano.
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Two new algorithms called Double Sarsa and Double Expected Sarsa that are shown to be more robust than their single counterparts when rewards are stochastic.
Highlights. New file editor utility: keras.saving.KerasFileEditor . Use it to inspect, diff, modify and resave Keras weights files. See basic workflow here.
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This repository contains Jupyter notebooks implementing the code samples found in the book Deep Learning with Python, 2nd Edition (Manning Publications).
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Chollet, F. & others, 2015. Keras. Available at: https://github.com/fchollet/keras. Citation in Bibtex format.
Nov 3, 2022This GitHub repository is now deprecated -- All Keras Applications models have moved into the core Keras repository and the TensorFlow pip package.
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