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OCoLC |
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20231017213018.0 |
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170422s2017 xx 073 o vleng d |
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|a UMI
|b eng
|e rda
|e pn
|c UMI
|d OCLCF
|d OCLCO
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|a (OCoLC)983730502
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|a CL0500000851
|b Safari Books Online
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|a Q325.5
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|a UAMI
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1 |
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|a Bertin, Marvin,
|e speaker.
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1 |
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|a Training, evaluating, and tuning deep neural network models with TensorFlow-Slim :
|b advanced topics in training, evaluating, and tuning deep neural network models /
|c with Marvin Bertin.
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|a [Place of publication not identified] :
|b O'Reilly,
|c [2017]
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300 |
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|a 1 online resource (1 streaming video file (1 hr., 12 min., 34 sec.)) :
|b digital, sound, color
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|a two-dimensional moving image
|b tdi
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a video
|b v
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Presenter, Marvin Bertin.
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|a Title from title screen (viewed April 21, 2017).
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|a Date of publication from resource description page.
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|a "This course builds on the training in Marvin Bertin's 'Introduction to TensorFlow-Slim', which covered the basic concepts and uses of the TensorFlow-Slim (TF-Slim) API. In a series of lessons designed for learners with basic machine learning knowledge and some previous TensorFlow experience, you'll explore many of TF-Slim's most advanced features; using them to build and train sophisticated deep learning models. As you work through the examples, you'll come to appreciate TF-Slim's primary benefit: its ability to enable the work of machine learning while avoiding code complexity, a significant problem in the world of increasingly deep neural networks."--Resource description page.
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590 |
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
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650 |
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|a Machine learning.
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650 |
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|a Artificial intelligence.
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650 |
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6 |
|a Apprentissage automatique.
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650 |
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|a Intelligence artificielle.
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650 |
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7 |
|a artificial intelligence.
|2 aat
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650 |
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7 |
|a Artificial intelligence.
|2 fast
|0 (OCoLC)fst00817247
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650 |
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7 |
|a Machine learning.
|2 fast
|0 (OCoLC)fst01004795
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856 |
4 |
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|u https://learning.oreilly.com/videos/~/9781491986080/?ar
|z Texto completo (Requiere registro previo con correo institucional)
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994 |
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|a 92
|b IZTAP
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