Result for 0B1B5B151BF62D64C52C12BAB11C62FF30BAFCFB

Query result

Key Value
FileName./usr/share/doc/keras-doc/examples/deep_dream.py
FileSize6240
MD543A7EEFDB143F5F028C82DB1D8A0503C
SHA-10B1B5B151BF62D64C52C12BAB11C62FF30BAFCFB
SHA-2560E2E286530EC56ED43186B12EDB7FD67C035C9F1D47E8B76AAF82FB326860655
SSDEEP192:VEVcYJp8TBBKlQxQhQH0PjA4pxTt5p3Fw:2S9CQUrAoxA
TLSHT108D1D83EEA47B219622361B51ACE07837FAD738B5362B850F05CD0105F8D96A9339BDC
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