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生成式深度學習 第2版（影印版）
生成式深度學習 第2版（影印版）
David Foster 著
出版時間：2024年03月
頁數(shù)：453
“本書通俗易懂地介紹了用于生成式建模的深度學習工具包。如果你是一個喜歡搗鼓代碼的創(chuàng)意工作者，希望在工作中應用深度學習，那么這本書就是你的最佳選擇?！?br /> ——David Ha
Stability A戰(zhàn)略主管
“這本杰作深入研究了最先進的生成式深度學習背后的所有主要技術。這是對人工智能最迷人領域之一的一次激動人
心的探索！”
——Francois Chollet
Keras創(chuàng)作

生成式AI是科技領域最炙手可熱的話題。這本實踐用書教機器學習工程師和數(shù)據(jù)科學人員如何利用TensorFlow和Keras從零開始創(chuàng)建令人印象深刻的生成式深度學習模型，包括變分自編碼器（VAE）、生成對抗網(wǎng)絡（GAN）、Transformers、歸一化流、基于能量的模型和去噪擴散模型。
本書從深度學習的基礎知識開始，逐步講解最前沿的架構(gòu)。通過各種技巧和竅門，你將理解如何使你的模型更高效地學習，變得更具創(chuàng)造力。
● 可了解VAE如何改變照片中的面部表情
● 訓練GAN基于你自己的數(shù)據(jù)集生成圖像
● 構(gòu)建擴散模型，產(chǎn)生新品種的花卉
● 訓練自己的GPT進行文本生成
● 學習ChatGPT等大語言模型的訓練方式
● 探索StyleGAN2和ViTVQGAN等最先進的架構(gòu)
● 使用Transformers和MuseGAN創(chuàng)作多聲部音樂
● 理解生成世界模型如何解決強化學習任務
● 深入研究DALL.E 2、Imagen、Stable Diffusion等多模態(tài)模型
書中還探討了生成式AI的未來，以及個人和公司如何積極利用這一引人注目的新技術創(chuàng)造競爭優(yōu)勢。
  1. Foreword
  2. Preface
  3. Part I. Introduction to Generative Deep Learning
  4. 1. Generative Modeling
  5. What Is Generative Modeling?
  6. Our First Generative Model
  7. Core Probability Theory
  8. Generative Model Taxonomy
  9. The Generative Deep Learning Codebase
  10. Summary
  11. 2. Deep Learning
  12. Data for Deep Learning
  13. Deep Neural Networks
  14. Multilayer Perceptron (MLP)
  15. Convolutional Neural Network (CNN)
  16. Summary
  17. Part II. Methods
  18. 3. Variational Autoencoders
  19. Introduction
  20. Autoencoders
  21. Variational Autoencoders
  22. Exploring the Latent Space
  23. Summary
  24. 4. Generative Adversarial Networks
  25. Introduction
  26. Deep Convolutional GAN (DCGAN)
  27. Wasserstein GAN with Gradient Penalty (WGAN-GP)
  28. Conditional GAN (CGAN)
  29. Summary
  30. 5. Autoregressive Models
  31. Introduction
  32. Long Short-Term Memory Network (LSTM)
  33. Recurrent Neural Network (RNN) Extensions
  34. PixelCNN
  35. Summary
  36. 6. Normalizing Flow Models
  37. Introduction
  38. Normalizing Flows
  39. RealNVP
  40. Other Normalizing Flow Models
  41. Summary
  42. 7. Energy-Based Models
  43. Introduction
  44. Energy-Based Models
  45. Summary
  46. 8. Diffusion Models
  47. Introduction
  48. Denoising Diffusion Models (DDM)
  49. Summary
  50. Part III. Applications
  51. 9. Transformers
  52. Introduction
  53. GPT
  54. Other Transformers
  55. Summary
  56. 10. Advanced GANs
  57. Introduction
  58. ProGAN
  59. StyleGAN
  60. StyleGAN2
  61. Other Important GANs
  62. Summary
  63. 11. Music Generation
  64. Introduction
  65. Transformers for Music Generation
  66. MuseGAN
  67. Summary
  68. 12. World Models
  69. Introduction
  70. Reinforcement Learning
  71. World Model Overview
  72. Collecting Random Rollout Data
  73. Training the VAE
  74. Collecting Data to Train the MDN-RNN
  75. Training the MDN-RNN
  76. Training the Controller
  77. In-Dream Training
  78. Summary
  79. 13. Multimodal Models
  80. Introduction
  81. DALL.E 2
  82. Imagen
  83. Stable Diffusion
  84. Flamingo
  85. Summary
  86. 14. Conclusion
  87. Timeline of Generative AI
  88. The Current State of Generative AI
  89. The Future of Generative AI
  90. Final Thoughts
  91. Index
書名：生成式深度學習 第2版（影印版）
作者：David Foster 著
國內(nèi)出版社：東南大學出版社
出版時間：2024年03月
頁數(shù)：453
書號：978-7-5766-1200-4
原版書書名：Generative Deep Learning, 2nd Edition
原版書出版商：O'Reilly Media
David Foster
 
David Foster是Applied Data Science的聯(lián)合創(chuàng)始人，這是一家數(shù)據(jù)科學咨詢公司，為客戶提供創(chuàng)新的解決方案。他擁有英國劍橋三一學院的數(shù)學碩士學位，以及華威大學運籌學碩士學位。
David曾多次贏得國際機器學習競賽，包括 InnoCentive Predicting Product Purchase 大獎賽，并獲得了可視化的第一名，這項技術可以幫助美國的制藥公司優(yōu)化臨床試驗的選址。
David活躍在在線數(shù)據(jù)科學社區(qū)，并撰寫了一系列有關深度強化學習的博客文章，包括《How To Build Your Own AlphaZero AI Using Python and Keras》(地址:http://bit. ly/2J6fGhU)。
 
 
The Pyrrhura genus falls under the family Psittacidae, one of three families of parrots. Within its subfamily Arinae are several macaw and parakeet species of the Western Hemisphere. The painted parakeet inhabits the coastal forests and mountains of northeastern South America.

Bright green feathers cover most of a painted parakeet, but they are blue above the beak, brown in the face, and reddish in the breast and tail. Most strikingly, the feathers on the painted parakeet’s neck look like scales; the brown center is outlined in offwhite. This combination of colors camouflages the birds in the rainforest.

Painted parakeets tend to feed in the forest canopy, where their green plumage masks them best. They forage in flocks of 5 to 12 birds for a wide variety of fruits, seeds, and flowers. Occasionally, when feeding below the canopy, painted parakeets will eat algae from forest pools. They grow to about 9 inches in length and live for 13 to 15 years. A clutch of painted parakeet chicks—each of which are less than an inch wide at hatching—is usually around five eggs.
購買選項
定價：132.00元
書號：978-7-5766-1200-4
出版社：東南大學出版社