SKU: 22618861054

GANs mit PyTorch selbst programmieren

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GANs mit PyTorch selbst programmierenEin verstndlicher Einstieg in Generative Adversarial Networks EAN: 9783960091479 Farbverschnitt: Generell werden die Bcher ohne Farbverschnitt geliefert, auch wenn die Abbildungen einen Farbverschnitt zeigen. Erscheinungsjahr: 30. 09. 2020 Produktform: Kartoniert Autoren: Rashid, Tariq bersetzung: Langenau, Frank Seitenzahl Blattzahl: 216 Abbildungen: komplett in Farbe Themenberschrift: COMPUTERS Programming Languages Python Keyword: Knstliche

Ein verständlicher Einstieg in Generative Adversarial Networks

EAN: 9783960091479
Farbverschnitt: Generell werden die Bücher ohne Farbverschnitt geliefert, auch wenn die Abbildungen einen Farbverschnitt zeigen.
Erscheinungsjahr: 30.09.2020
Produktform: Kartoniert
Autoren: Rashid, Tariq
Übersetzung: Langenau, Frank
Seitenzahl/Blattzahl: 216
Abbildungen: komplett in Farbe
Themenüberschrift: COMPUTERS / Programming Languages / Python
Keyword: Künstliche Intelligenz; Data Mining; Deep Learning; Neuronale Netze; Künstliche Neuronale Netze; Python; Big Data; AI; Artificial Intelligence; Machine Learning; Maschinelles Lernen; GAN
Fachschema: Programmiersprachen~Data Mining (EDV)
Fachkategorie: Data Mining, Programmier- und Skriptsprachen, allgemein
Thema: Verstehen
Text Sprache: ger
Originalsprache: eng
Verlag: Dpunkt.Verlag GmbH, O'Reilly
Länge: 241 mm
Breite: 166 mm
Höhe: 15 mm
Gewicht: 408 gr
Genre: Mathematik/Naturwissenschaften/Technik/Medizin
andere Sprache: 9798624728158
Herkunftsland: DEUTSCHLAND (DE)
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SKU: 22618861054

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Grantham, US
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Not greasy, easy to use. Good for travel.
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Tanya
Phoenix, US
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Pies sin grietas e hidratados
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Me encanto, hidratación completa de mis piecitos
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Kindle Customer
New York, US
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Best Foot Cream I’ve Ever Used!
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This is honestly the best foot cream I’ve ever used! My feet are incredibly smooth, and my heels look like they’ve never been cracked. I’ve struggled with dry heels before, and this made such a noticeable difference. Highly recommend!
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Reviewed in the United States on May 3, 2026

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