|
|
|
|
LEADER |
00000cam a2200000 i 4500 |
001 |
EBSCO_on1114971280 |
003 |
OCoLC |
005 |
20231017213018.0 |
006 |
m o d |
007 |
cr ||||||||||| |
008 |
190907s2020 vaua o 001 0 eng d |
040 |
|
|
|a EBLCP
|b eng
|e rda
|e pn
|c EBLCP
|d YDX
|d OCLCQ
|d WAU
|d N$T
|d OSU
|d OCLCQ
|d OCLCO
|d OCLCQ
|d OCLCO
|
019 |
|
|
|a 1117318396
|a 1117893939
|a 1121582946
|a 1128822952
|a 1129093869
|
020 |
|
|
|a 9781683924616
|q (electronic book)
|
020 |
|
|
|a 1683924614
|q (electronic book)
|
020 |
|
|
|a 9781683924593
|q (electronic bk.)
|
020 |
|
|
|a 1683924592
|q (electronic bk.)
|
020 |
|
|
|z 9781683924609
|q (paperback)
|
020 |
|
|
|z 1683924606
|q (paperback)
|
029 |
1 |
|
|a CHNEW
|b 001074196
|
029 |
1 |
|
|a CHVBK
|b 579470075
|
035 |
|
|
|a (OCoLC)1114971280
|z (OCoLC)1117318396
|z (OCoLC)1117893939
|z (OCoLC)1121582946
|z (OCoLC)1128822952
|z (OCoLC)1129093869
|
050 |
|
4 |
|a Q325.5
|
082 |
0 |
4 |
|a 006.3/1
|2 23
|
049 |
|
|
|a UAMI
|
100 |
1 |
|
|a Campesato, Oswald,
|e author.
|
245 |
1 |
0 |
|a TensorFlow 2.0 pocket primer /
|c Oswald Campesato.
|
264 |
|
1 |
|a Dulles, Virginia :
|b Mercury Learning and Information,
|c [2020]
|
264 |
|
4 |
|c Ã2020
|
300 |
|
|
|a 1 online resource (xx, 230 pages) :
|b illustrations
|
336 |
|
|
|a text
|b txt
|2 rdacontent
|
337 |
|
|
|a computer
|b c
|2 rdamedia
|
338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
490 |
1 |
|
|a Pocket primer series
|
500 |
|
|
|a Includes index.
|
505 |
0 |
|
|a Preface -- Introduction to TensorFlow 2 -- Useful TF 2 APIs -- TF2 datasets -- Linear regression -- Working with classifiers -- Appendix: TF 2, Keras, and advanced topics.
|
520 |
|
|
|a As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various "core" features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge
|
588 |
0 |
|
|a Print version record.
|
590 |
|
|
|a eBooks on EBSCOhost
|b EBSCO eBook Subscription Academic Collection - Worldwide
|
630 |
0 |
0 |
|a TensorFlow.
|
650 |
|
0 |
|a Machine learning.
|
650 |
|
0 |
|a Artificial intelligence.
|
650 |
|
6 |
|a Apprentissage automatique.
|
650 |
|
6 |
|a Intelligence artificielle.
|
650 |
|
7 |
|a artificial intelligence.
|2 aat
|
650 |
|
7 |
|a Artificial intelligence
|2 fast
|
650 |
|
7 |
|a Machine learning
|2 fast
|
776 |
0 |
8 |
|i Print version:
|a Campesato, Oswald.
|t TensorFlow 2.0 pocket primer.
|d Dulles, Virginia : Mercury Learning and Information, [2020]
|z 9781683924609
|w (OCoLC)1123219173
|
830 |
|
0 |
|a Pocket primer.
|
856 |
4 |
0 |
|u https://ebsco.uam.elogim.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2240036
|z Texto completo
|
938 |
|
|
|a ProQuest Ebook Central
|b EBLB
|n EBL5885552
|
938 |
|
|
|a EBSCOhost
|b EBSC
|n 2240036
|
938 |
|
|
|a YBP Library Services
|b YANK
|n 16425319
|
938 |
|
|
|a YBP Library Services
|b YANK
|n 300795860
|
994 |
|
|
|a 92
|b IZTAP
|