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index.html
12
index.html
@@ -5,10 +5,12 @@ To be published by MIT Press.
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<h2> Download draft PDF </h2>
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<h2> Download draft PDF </h2>
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<a href="https://github.com/udlbook/udlbook/releases/download/v0.5.0/UnderstandingDeepLearning_23_01_23_C.pdf">Draft PDF Chapters 1-18</a><br> 2023-01-23. CC-BY-NC-ND license
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<a href="https://github.com/udlbook/udlbook/releases/download/v0.7.14/UnderstandingDeepLearning_17_04_23_C.pdf">Draft PDF Chapters 1-20</a><br> 2023-04-17. CC-BY-NC-ND license
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<br>
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<img src="https://img.shields.io/github/downloads/udlbook/udlbook/total" alt="download stats shield">
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<br>
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<br>
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<ul>
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<ul>
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<li> Chapters 18-20 (coming soon)
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<li> Appendices and notebooks coming soon
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<li> Report errata via <a href="https://github.com/udlbook/udlbook/issues">github</a> or contact me directly at udlbookmail@gmail.com
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<li> Report errata via <a href="https://github.com/udlbook/udlbook/issues">github</a> or contact me directly at udlbookmail@gmail.com
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<li> Follow me on <a href="https://twitter.com/SimonPrinceAI">Twitter</a> or <a href="https://www.linkedin.com/in/simon-prince-615bb9165/">LinkedIn</a> for updates.
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<li> Follow me on <a href="https://twitter.com/SimonPrinceAI">Twitter</a> or <a href="https://www.linkedin.com/in/simon-prince-615bb9165/">LinkedIn</a> for updates.
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</ul>
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</ul>
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@@ -31,10 +33,11 @@ To be published by MIT Press.
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<li> Chapter 14 - Unsupervised learning
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<li> Chapter 14 - Unsupervised learning
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<li> Chapter 15 - Generative adversarial networks
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<li> Chapter 15 - Generative adversarial networks
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<li> Chapter 16 - Normalizing flows
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<li> Chapter 16 - Normalizing flows
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<li> Chapter 17 - Variational auto-encoders
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<li> Chapter 17 - Variational autoencoders
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<li> Chapter 18 - Diffusion models
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<li> Chapter 18 - Diffusion models
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<li> Chapter 19 - Deep reinforcement learning
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<li> Chapter 19 - Deep reinforcement learning
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<li> Chapter 20 - Why does deep learning work?
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<li> Chapter 20 - Why does deep learning work?
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<li> Chapter 21 - Deep learning and ethics
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</ul>
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</ul>
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<br>
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<br>
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@@ -67,8 +70,9 @@ Citation:
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<li> Chapter 14 - Unsupervised learning: Slides / Notebooks / PDF Figures / Powerpoint Figures
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<li> Chapter 14 - Unsupervised learning: Slides / Notebooks / PDF Figures / Powerpoint Figures
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<li> Chapter 15 - Generative adversarial networks: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 15 - Generative adversarial networks: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 16 - Normalizing flows: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 16 - Normalizing flows: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 17 - Variational auto-encoders: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 17 - Variational autoencoders: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 18 - Diffusion models: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 18 - Diffusion models: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 19 - Deep reinforcement learning: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 19 - Deep reinforcement learning: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 20 - Why does deep learning work?: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 20 - Why does deep learning work?: Slides / Notebooks / PDF Figures / PowerPoint Figures
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<li> Chapter 21 - Deep learning and ethics: Slides / Notebooks / PDF Figures / PowerPoint Figures
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</ul>
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</ul>
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