Balík: python3-keras-preprocessing (1.1.0+ds-1)
Odkazy pre python3-keras-preprocessing
Zdroje Debian:
Stiahnuť zdrojový balík keras-preprocessing:
- [keras-preprocessing_1.1.0+ds-1.dsc]
- [keras-preprocessing_1.1.0+ds.orig.tar.xz]
- [keras-preprocessing_1.1.0+ds-1.debian.tar.xz]
Správcovia:
Externé zdroje:
- Domovská stránka [keras.io]
Podobné balíky:
data preprocessing module for the Keras deep learning framework
Keras is a Python library for machine learning based on deep (multi- layered) artificial neural networks (DNN), which follows a minimalistic and modular design with a focus on fast experimentation.
Features of DNNs like neural layers, cost functions, optimizers, initialization schemes, activation functions and regularization schemes are available in Keras a standalone modules which can be plugged together as wanted to create sequence models or more complex architectures. Keras supports convolutions neural networks (CNN, used for image recognition resp. classification) and recurrent neural networks (RNN, suitable for sequence analysis like in natural language processing).
It runs as an abstraction layer on the top of Theano (math expression compiler) by default, which makes it possible to accelerate the computations by using (GP)GPU devices. Alternatively, Keras could run on Google's TensorFlow (not yet available in Debian).
Keras Preprocessing is the data preprocessing and data augmentation module of the Keras deep learning library. It provides utilities for working with image data, text data, and sequence data.
Ostatné balíky súvisiace s balíkom python3-keras-preprocessing
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- dep: python3
- interactive high-level object-oriented language (default python3 version)
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- dep: python3-numpy
- schopnosti rýchlych polí do jazyka Python 3
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- dep: python3-six (>= 1.9.0)
- knižnica na kompatibilitu Pythonu 2 a 3 (rozhranie Python 3)
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- rec: python3-keras
- deep learning framework running on Theano or TensorFlow
Stiahnuť python3-keras-preprocessing
Architektúra | Veľkosť balíka | Nainštalovaná veľkosť | Súbory |
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all | 30.6 kB | 169.0 kB | [zoznam súborov] |