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Generative Deep Learning

AI 与机器学习 iteblog 53℃ 0评论

关注 过往记忆大数据 微信公众号,回复 8494 获取本书下载地址。

子标题:Teaching Machines to Paint, Write, Compose, and Play

Generative Deep Learning
作者:
David Foster
ISBN-10:
1492041947
出版年份:
2019
页数:
330
语言:
English
文件大小:
31.1 MB
文件格式:
PDF

图书描述

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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