Advanced deep learning with TensorFlow 2 and Keras : : apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more / / Rowel Atienza.
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| Place / Publishing House: | Birmingham, England ;, Mumbai : : Packt,, [2020] 2020 |
| Year of Publication: | 2020 |
| Edition: | Second edition. |
| Language: | English |
| Online Access: | |
| Physical Description: | 1 online resource (513 pages) |
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| 003 | MiAaPQ | ||
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| 008 | 200422s2020 enk o 000 0 eng d | ||
| 020 | |z 9781838821654 | ||
| 020 | |a 9781838825720 (e-book) | ||
| 035 | |a (MiAaPQ)5006126530 | ||
| 035 | |a (Au-PeEL)EBL6126530 | ||
| 035 | |a (OCoLC)1143638337 | ||
| 040 | |a MiAaPQ |b eng |e rda |e pn |c MiAaPQ |d MiAaPQ | ||
| 050 | 4 | |a QA76.76.A65 |b .A854 2020 | |
| 082 | 0 | |a 005.3 |2 23 | |
| 100 | 1 | |a Atienza, Rowel, |e author. | |
| 245 | 1 | 0 | |a Advanced deep learning with TensorFlow 2 and Keras : |b apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more / |c Rowel Atienza. |
| 250 | |a Second edition. | ||
| 264 | 1 | |a Birmingham, England ; |a Mumbai : |b Packt, |c [2020] | |
| 264 | 4 | |c 2020 | |
| 300 | |a 1 online resource (513 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | |a Description based on print version record. | ||
| 590 | |a Electronic reproduction. Ann Arbor, MI : ProQuest, 2018. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. | ||
| 630 | 0 | 0 | |a TensorFlow. |
| 655 | 4 | |a Electronic books. | |
| 776 | 0 | 8 | |i Print version: |a Atienza, Rowel. |t Advanced deep learning with TensorFlow 2 and Keras : apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more. |b Second edition. |d Birmingham, England ; Mumbai : Packt, c2020 |h 513 pages |z 9781838821654 |
| 797 | 2 | |a ProQuest (Firm) | |
| 856 | 4 | 0 | |u https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=6126530 |z Click to View |