Result for 100F718E6947D16C513545B8052D9D1566B81E0C

Query result

Key Value
FileName./usr/share/doc/keras-doc/examples/mnist_cnn.py
FileSize2270
MD53BD78610CA54DE48ACF01D66EEF1F170
SHA-1100F718E6947D16C513545B8052D9D1566B81E0C
SHA-25613636EB1488F5738FB5805C0B38706F346334D2A688127A0F28B3730541AA7A0
SSDEEP48:6qqr1fW45gh2B68OIHCI8rtGissv+yWqu3Wsit8IJzk:6qqMZx8OoCBrtGl6+yWqXJtO
TLSHT12A412EB3C0231A5DFA2670B9A1C91AD63BE993434F6636A1FB7C4010DB87209A73D919
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize942032
MD59EE8D4352481D1DAC8F8C26E165B1DA1
PackageDescriptionCPU/GPU math expression compiler for Python (docs) 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, but coming up). . This package contains the documentation for Keras.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamekeras-doc
PackageSectiondoc
PackageVersion2.1.1-1
SHA-1D1759E97E0267A861FA9A6EB5568E23251D070B1
SHA-256EF91FD03A896D2F8D5E0C260E64F27DEA9395684BD6FDCAD82E0CB480C84E03E