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     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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python-keras 3.15.1
Propagated dependencies: python-absl-py@2.3.1 python-h5py@3.16.0 python-ml-dtypes@0.5.4 python-namex@0.0.7 python-numpy@2.4.6 python-optree@0.14.0 python-packaging@26.2 python-rich@15.0.0
Channel: guix-science
Location: guix-science/packages/machine-learning.scm (guix-science packages machine-learning)
Home page: https://keras.io/
Licenses: ASL 2.0
Build system: pyproject
Synopsis: Multi-backend deeplearning framework for Python
Description:

Keras 3 is a multi-backend deep learning framework, with support for JAX, TensorFlow, PyTorch, and OpenVINO (for inference-only). Effortlessly build and train models for computer vision, natural language processing, audio processing, timeseries forecasting, recommender systems, etc.

  • Accelerated model development: Ship deep learning solutions faster thanks to the high-level UX of Keras and the availability of easy-to-debug runtimes like PyTorch or JAX eager execution.

  • State-of-the-art performance: By picking the backend that is the fastest for your model architecture (often JAX!), leverage speedups ranging from 20% to 350% compared to other frameworks.

  • Datacenter-scale training: Scale confidently from your laptop to large clusters of GPUs or TPUs.

python-keras 3.13.1
Propagated dependencies: python-absl-py@2.3.1 python-h5py@3.16.0 python-ml-dtypes@0.5.4 python-namex@0.0.7 python-numpy@2.4.6 python-optree@0.14.0 python-packaging@26.2 python-rich@15.0.0
Channel: guix-science
Location: guix-science/packages/machine-learning.scm (guix-science packages machine-learning)
Home page: https://github.com/keras-team/keras
Licenses: ASL 2.0
Build system: pyproject
Synopsis: Deep learning API
Description:

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.

Total packages: 2