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Revision dafc26a4ce301e9e934e5f3b8e5ac7e70fe971a3 authored by Alex Boulangé on 16 March 2019, 14:03:30 UTC, committed by cran-robot on 16 March 2019, 14:03:30 UTC
version 1.2.8
1 parent 793e489
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  • README.md
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To reference or cite the objects present in the Software Heritage archive, permalinks based on SoftWare Hash IDentifiers (SWHIDs) must be used.
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This interface enables to generate software citations, provided that the root directory of browsed objects contains a citation.cff or codemeta.json file.
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Generate software citation in BibTex format (requires biblatex-software package)
Generating citation ...
Generate software citation in BibTex format (requires biblatex-software package)
Generating citation ...
Generate software citation in BibTex format (requires biblatex-software package)
Generating citation ...
README.md
automl package fits from simple regression to highly customizable deep neural networks 
either with gradient descent or metaheuristic, using automatic hyper parameters 
tuning and custom cost function.
A mix inspired by the common tricks on Deep Learning and Particle Swarm Optimization.

(Key words: autoML, Deep Learning, Particle Swarm Optimization, learning rate, minibatch, 
batch normalization, lambda, RMSprop, momentum, adam optimization, learning rate decay, 
inverted dropout, particles number, kappa, regression, logistic regression)
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Software Heritage — Copyright (C) 2015–2025, The Software Heritage developers. License: GNU AGPLv3+.
The source code of Software Heritage itself is available on our development forge.
The source code files archived by Software Heritage are available under their own copyright and licenses.
Terms of use: Archive access, API— Contact— JavaScript license information— Web API

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