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-<h1>Understanding Deep Learning</h1>
+<h1>Understanding Deep Learning</h1>
+by Simon J.D. Prince
+<br>
+To be published by MIT Press.
+
+
+<h2>Key links</h2>
+<ul>
+	<li> <a href="https://github.com/udlbook/udlbook/releases/download/v0.1.0/UnderstandingDeepLearning_30_07_22_C.pdf">Draft PDF Chapters 2-9</a>
+	<li> Draft PDF Chapters 10-13 (coming Sept 1st, 2022)
+	<li> Draft PDF Chapters 1,14-19 (coming Jan 2nd, 2023)
+	<li> Jupyter notebooks (coming Spring 2023)
+	<li> Report errata via <a href="https://github.com/udlbook/udlbook/issues">github</a> or contact me directly at [email protected]
+</ul>
+
+<h2>Table of contents</h2>
+<ul> 
+	<li>  Chapter 1 - Introduction
+	<li>  Chapter 2 - Supervised learning <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap2PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap2.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 3 - Shallow neural networks <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap3PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap3.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 4 - Deep neural networks <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap4PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap4.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 5 - Loss functions <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap5PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap5.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 6 - Training models <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap6PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap6.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 7 - Gradients and initialization <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap7PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap7.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 8 - Measuring performance <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap8PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap8.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 9 - Regularization <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap9PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap9.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 10 - Convolutional nets
+	<li>  Chapter 11 - Residual networks and BatchNorm
+	<li>  Chapter 12 - Transformers
+	<li>  Chapter 13 - Graph neural networks
+	<li>  Chapter 14 - Variational auto-encoders
+	<li>  Chapter 15 - Normalizing flows
+	<li>  Chapter 16 - Generative adversarial networks
+	<li>  Chapter 17 - Diffusion models
+	<li>  Chapter 18 - Deep reinforcement learning
+	<li>  Chapter 19 - Why does deep learning work?
+</ul>
+
+<br>
+Citation:
+<pre><code>
+ @book{prince2022understanding,
+ author = "Simon J.D. Prince",
+ title = "Understanding Deep Learning",
+ publisher = "MIT Press",
+ year = 2022,
+ url = "https://udlbook.github.io/udlbook/"
+}
+</code></pre>
+
+