Result for 0B6D781CA73D8CBBB9F0DDAAC2BA5898B480505C

Query result

Key Value
FileName./usr/share/doc/keras-doc/html/constraints/index.html
FileSize11486
MD50B8E5AF0D0D0BFC61953D86A5160183C
SHA-10B6D781CA73D8CBBB9F0DDAAC2BA5898B480505C
SHA-256FF0054850D3AE7ECD2AAEEA2714FF7302892CFC03C0384F5824A36DB265D03DF
SSDEEP192:zSoLgghhT9QxwhyxWbrD0MbAyIe5x3b52D:zSocghpuChWWbXMyIe1k
TLSHT1DB32210009E0363B816385E68A682B247EE3414BF5057D91F2FC264EEFE2F4A6D0B54D
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