Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play

Foster, David

Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play

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商品描述

Generative modeling is one of the hottest topics in artificial intelligence. Recent advances in the field have shown how it's possible to teach a machine to excel at human endeavors--such as drawing, composing music, and completing tasks--by generating an understanding of how its actions affect its environment.

With this practical book, machine learning engineers and data scientists will learn how to recreate some of the most famous examples of generative deep learning models, such as variational autoencoders and generative adversarial networks (GANs). You'll also learn how to apply the techniques to your own datasets.

David Foster, cofounder of Applied Data Science, demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to the most cutting-edge algorithms in the field. Through tips and tricks, you'll learn how to make your models learn more efficiently and become more creative.

  • Get a fundamental overview of generative modeling
  • Learn how to use the Keras and TensorFlow libraries for deep learning
  • Discover how variational autoencoders (VAEs) work
  • Get practical examples of generative adversarial networks (GANs)
  • Understand how to build generative models that learn how to paint, write, and compose
  • Apply generative models within a reinforcement learning setting to accomplish tasks

商品描述(中文翻譯)

生成建模是人工智慧中最熱門的話題之一。該領域的最新進展顯示，通過生成對其環境的影響的理解，可以教導機器在人類努力方面表現出色，例如繪畫、作曲和完成任務。

這本實用書籍將教導機器學習工程師和數據科學家如何重新創建一些最著名的生成深度學習模型，例如變分自編碼器和生成對抗網絡（GAN）。您還將學習如何將這些技術應用於自己的數據集。

Applied Data Science的聯合創始人David Foster展示了每種技術的內部運作方式，從深度學習的基礎知識開始，然後進一步介紹該領域中最尖端的算法。通過技巧和訣竅，您將學習如何使模型學習更高效並變得更有創造力。

- 獲得生成建模的基本概述
- 學習如何使用Keras和TensorFlow庫進行深度學習
- 了解變分自編碼器（VAEs）的工作原理
- 獲得生成對抗網絡（GANs）的實際示例
- 理解如何構建能夠學習繪畫、寫作和作曲的生成模型
- 在強化學習環境中應用生成模型以完成任務

作者簡介

David Foster is the co-founder of Applied Data Science, a data science consultancy delivering bespoke solutions for clients. He holds an MA in Mathematics from Trinity College, Cambridge, UK and an MSc in Operational Research from the University of Warwick.

David has won several international machine learning competitions, including the Innocentive Predicting Product Purchase challenge and was awarded first prize for a visualisation that enables a pharmaceutical company in the US to optimize site selection for clinical trials.

He is an active participant in the online data science community and has authored several successful blog posts on deep reinforcement learning including 'How To Build Your Own AlphaZero AI'.

作者簡介(中文翻譯)

David Foster是Applied Data Science的共同創辦人，該公司提供客製化的數據科學解決方案。他擁有英國劍橋大學Trinity College的數學碩士學位，以及英國華威大學的運籌學碩士學位。

David曾獲得多個國際機器學習競賽的冠軍，包括Innocentive預測產品購買挑戰賽，並因為一項能夠幫助美國一家製藥公司優化臨床試驗場地選擇的可視化方案而獲得第一名。

他是線上數據科學社群的活躍參與者，並撰寫了幾篇成功的博客文章，包括"如何建立自己的AlphaZero人工智能"等深度強化學習相關主題。

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