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http://hdl.handle.net/123456789/1408Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ahirwar, Kailash | - |
| dc.date.accessioned | 2026-07-24T09:37:57Z | - |
| dc.date.available | 2026-07-24T09:37:57Z | - |
| dc.date.issued | 2019-01 | - |
| dc.identifier.isbn | 978-1-78913-667-8 | - |
| dc.identifier.uri | http://hdl.handle.net/123456789/1408 | - |
| dc.description.abstract | Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field because it is one of the most rapidly growing areas of machine learning (ML). This book will test unsupervised techniques of training neural networks as you build eight end-to-end projects in the GAN domain. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Pact Publication | en_US |
| dc.subject | Generative Adversarial Networks Projects | en_US |
| dc.title | Generative Adversarial Networks Projects | en_US |
| dc.title.alternative | Build next-generation generative models using TensorFlow and Keras | en_US |
| dc.type | Book | en_US |
| Appears in Collections: | E-Books | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Generative Adversarial Networks Projects.pdf | 12.16 MB | Adobe PDF | View/Open |
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