diff --git a/index.html b/index.html
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+++ b/index.html
@@ -3,12 +3,12 @@ by Simon J.D. Prince
 <br>
 To be published by MIT Press.
 
+<h2> Download draft PDF </h2>
 
-<h2>Key links</h2>
+<a href="https://github.com/udlbook/udlbook/releases/download/v0.2.1/UnderstandingDeepLearning_07_10_22_C.pdf">Draft PDF Chapters 2-13</a>  2022-10-07. CC-BY-NC-ND license
+<br>
 <ul>
-	<li> <a href="https://github.com/udlbook/udlbook/releases/download/v0.2.1/UnderstandingDeepLearning_07_10_22_C.pdf">Draft PDF Chapters 2-13</a>  2022-10-07. CC-BY-NC-ND license
-	<li> Draft PDF Chapters 1,14-19 (coming Jan 2nd, 2023)
-	<li> Jupyter notebooks (coming Spring 2023)
+	<li> Chapters 1,14-19 (coming Jan 2nd, 2023)
 	<li> Report errata via <a href="https://github.com/udlbook/udlbook/issues">github</a> or contact me directly at udlbookmail@gmail.com
 	<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.
 </ul>
@@ -16,18 +16,17 @@ To be published by MIT Press.
 <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  <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap10PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap10.pptx">PowerPoint Figures</a> 
-	<li>  Chapter 11 - Residual networks <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap11PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap11.pptx">PowerPoint Figures</a> 
-	<li>  Chapter 12 - Transformers  <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap12PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap12.pptx">PowerPoint Figures</a> 
-	<li>  Chapter 13 - Graph neural networks  <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap13PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap13.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 2 - Supervised learning 
+	<li>  Chapter 3 - Shallow neural networks 
+	<li>  Chapter 4 - Deep neural networks 
+	<li>  Chapter 5 - Loss functions
+	<li>  Chapter 6 - Training models 
+	<li>  Chapter 7 - Gradients and initialization 
+	<li>  Chapter 8 - Measuring performance 
+	<li>  Chapter 9 - Regularization 
+	<li>  Chapter 11 - Residual networks
+	<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
@@ -48,3 +47,25 @@ Citation:
 }
 </code></pre>
 	
+<h2>Resources for instructors </h2>
+<ul> 
+	<li>  Chapter 1 - Introduction 
+	<li>  Chapter 2 - Supervised learning: Slides / Notebooks / <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:  Slides / Notebooks /  <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:  Slides / Notebooks /  <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:  Slides / Notebooks /  <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:  Slides / Notebooks /  <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:  Slides / Notebooks /  <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:  Slides / Notebooks /  <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: Slides / Notebooks /  <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:  Slides / Notebooks / <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap10PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap10.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 11 - Residual networks: Slides / Notebooks /  <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap11PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap11.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 12 - Transformers:  Slides / Notebooks / <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap12PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap12.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 13 - Graph neural networks:  Slides / Notebooks /   <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap13PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap13.pptx">PowerPoint Figures</a> 
+	<li>  Chapter 14 - Variational auto-encoders:  Slides / Notebooks / PDF Figures / PowerPoint Figures
+	<li>  Chapter 15 - Normalizing flows:  Slides / Notebooks / PDF Figures / PowerPoint Figures
+	<li>  Chapter 16 - Generative adversarial networks:  Slides / Notebooks / PDF Figures / PowerPoint Figures
+	<li>  Chapter 17 - Diffusion models: Slides / Notebooks / PDF Figures / PowerPoint Figures
+	<li>  Chapter 18 - Deep reinforcement learning:  Slides / Notebooks / PDF Figures / PowerPoint Figures
+	<li>  Chapter 19 - Why does deep learning work?:  Slides / Notebooks / PDF Figures / PowerPoint Figures
+</ul>