Generative Deep Learning

With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial ...

Generative Deep Learning

Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

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Generative Deep Learning
Language: en
Pages: 330
Authors: David Foster
Categories: Computers
Type: BOOK - Published: 2019-06-28 - Publisher: "O'Reilly Media, Inc."

Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of
Generatives Deep Learning
Language: de
Pages: 310
Authors: David Foster
Categories: Computers
Type: BOOK - Published: 2020 - Publisher:

Generative Modelle haben sich zu einem der spannendsten Themenbereiche der Künstlichen Intelligenz entwickelt: Mit generativem Deep Learning ist es inzwischen möglich, einer Maschine das Malen, Schreiben oder auch das Komponieren von Musik beizubringen - kreative Fähigkeiten, die bisher dem Menschen vorbehalten waren. Mit diesem praxisnahen Buch können Data Scientists einige
Generative Adversarial Networks with Python
Language: en
Pages: 652
Authors: Jason Brownlee
Categories: Computers
Type: BOOK - Published: 2019-07-11 - Publisher: Machine Learning Mastery

Step-by-step tutorials on generative adversarial networks in python for image synthesis and image translation.
GANs in Action
Language: en
Pages: 276
Authors: Jakub Langr, Vladimir Bok
Categories: Computers
Type: BOOK - Published: 2019-10-07 - Publisher: Manning Publications

Deep learning systems have gotten really great at identifying patterns in text, images, and video. But applications that create realistic images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a promising solution to these challenges by pairing two competing neural networks' one
Generative Deep Learning
Language: en
Pages: 330
Authors: David Foster
Categories: Computers
Type: BOOK - Published: 2019-06-28 - Publisher: O'Reilly Media

Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of