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<h2> Download draft PDF </h2>
<a href="https://github.com/udlbook/udlbook/releases/download/v1.1/UnderstandingDeepLearning_23_07_23_C.pdf">Draft PDF Chapters 1-21</a><br> 2023-07-23. CC-BY-NC-ND license
<a href="https://github.com/udlbook/udlbook/releases/download/v1.1.1/UnderstandingDeepLearning_26_07_23_C.pdf">Draft PDF Chapters 1-21</a><br> 2023-07-26. CC-BY-NC-ND license
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<img src="https://img.shields.io/github/downloads/udlbook/udlbook/total" alt="download stats shield">
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@@ -83,10 +83,10 @@ Instructions for editing figures / equations can be found <a href="https://drive
<ul>
<li> Chapter 1 - Introduction: <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap01/1_1_BackgroundMathematics.ipynb">1.1</a>
<li> Chapter 2 - Supervised learning <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap02/2_1_Supervised_Learning.ipynb">2.1</a>
<li> Chapter 3 - Shallow neural networks <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap03/3_1_Shallow_Networks_I.ipynb">3.1</a>, <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap03/3_2_Shallow_Networks_II.ipynb">3.2</a>, <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap03/3_3_Shallow_Network_Regions.ipynb">3.3</a>, <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap03/3_4_Activation_Functions.ipynb">3.4</a>
<li> Chapter 4 - Deep neural networks <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap04/4_1_Composing_Networks.ipynb">4.1</a>, 4.2, 4.3 (coming soon)
<li> Chapter 5 - Loss functions (coming soon)
<li> Chapter 2 - Supervised learning: <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap02/2_1_Supervised_Learning.ipynb">2.1</a>
<li> Chapter 3 - Shallow neural networks: <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap03/3_1_Shallow_Networks_I.ipynb">3.1</a>, <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap03/3_2_Shallow_Networks_II.ipynb">3.2</a>, <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap03/3_3_Shallow_Network_Regions.ipynb">3.3</a>, <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap03/3_4_Activation_Functions.ipynb">3.4</a>
<li> Chapter 4 - Deep neural networks: <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap04/4_1_Composing_Networks.ipynb">4.1</a>, <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap04/4_2_Clipping_functions.ipynb">4.2</a>, <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap04/4_3_Deep_Networks.ipynb">4.3</a>
<li> Chapter 5 - Loss functions: <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap04/4_3_Deep_Networks.ipynb">5.1</a>, <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap05/5_2_Binary_Cross_Entropy_Loss.ipynb">5.2</a>, <a href="https://github.com/udlbook/udlbook/blob/main/Notebooks/Chap05/5_3_Multiclass_Cross_entropy_Loss.ipynb">5.3</a>
<li> Chapter 6 - Training models (coming soon)
<li> Chapter 7 - Gradients and initialization (coming soon)
<li> Chapter 8 - Measuring performance (coming soon)