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Morten Hjorth-Jensen
2024-09-30 07:06:58 +02:00
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doc/pub/week40/html/._week40-bs003.html
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@@ -369,7 +369,7 @@ MathJax.Hub.Config({
<ol>
<li> The lecture notes for week 40 (these notes)</li>
<li> For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.</li>
<li> For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al pages 48-60</li>
<li> For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week)</li>
<li> Video on gradient descent at <a href="https://www.youtube.com/watch?v=sDv4f4s2SB8" target="_self"><tt>https://www.youtube.com/watch?v=sDv4f4s2SB8</tt></a></li>
<li> Video on stochastic gradient descent at <a href="https://www.youtube.com/watch?v=vMh0zPT0tLI" target="_self"><tt>https://www.youtube.com/watch?v=vMh0zPT0tLI</tt></a></li>
<li> Neural Networks demystified at <a href="https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs" target="_self"><tt>https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs</tt></a></li>
doc/pub/week40/html/week40-reveal.html
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<p><li> For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.</li>
<p><li> For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al pages 48-60</li>
<p><li> For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week)</li>
<p><li> Video on gradient descent at <a href="https://www.youtube.com/watch?v=sDv4f4s2SB8" target="_blank"><tt>https://www.youtube.com/watch?v=sDv4f4s2SB8</tt></a></li>
doc/pub/week40/html/week40-solarized.html
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@@ -335,7 +335,7 @@ MathJax.Hub.Config({
<ol>
<li> The lecture notes for week 40 (these notes)</li>
<li> For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.</li>
<li> For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al pages 48-60</li>
<li> For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week)</li>
<li> Video on gradient descent at <a href="https://www.youtube.com/watch?v=sDv4f4s2SB8" target="_blank"><tt>https://www.youtube.com/watch?v=sDv4f4s2SB8</tt></a></li>
<li> Video on stochastic gradient descent at <a href="https://www.youtube.com/watch?v=vMh0zPT0tLI" target="_blank"><tt>https://www.youtube.com/watch?v=vMh0zPT0tLI</tt></a></li>
<li> Neural Networks demystified at <a href="https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs" target="_blank"><tt>https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs</tt></a></li>
doc/pub/week40/html/week40.html
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@@ -412,7 +412,7 @@ MathJax.Hub.Config({
<ol>
<li> The lecture notes for week 40 (these notes)</li>
<li> For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.</li>
<li> For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al pages 48-60</li>
<li> For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week)</li>
<li> Video on gradient descent at <a href="https://www.youtube.com/watch?v=sDv4f4s2SB8" target="_blank"><tt>https://www.youtube.com/watch?v=sDv4f4s2SB8</tt></a></li>
<li> Video on stochastic gradient descent at <a href="https://www.youtube.com/watch?v=vMh0zPT0tLI" target="_blank"><tt>https://www.youtube.com/watch?v=vMh0zPT0tLI</tt></a></li>
<li> Neural Networks demystified at <a href="https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs" target="_blank"><tt>https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs</tt></a></li>
doc/pub/week40/ipynb/ipynb-week40-src.tar.gz
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doc/pub/week40/ipynb/week40.ipynb
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doc/src/week40/week40.do.txt
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@@ -22,7 +22,7 @@ DATE: September 30-October 4, 2024
!bblock Readings and Videos:
o The lecture notes for week 40 (these notes)
o For a good discussion on gradient methods, we would like to recommend Goodfellow et al section 4.3-4.5 and sections 8.3-8.6. We will come back to the latter chapter in our discussion of Neural networks as well.
o For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al pages 48-60
o For neural networks we recommend Goodfellow et al chapter 6 and Raschka et al chapter 2 (contains also material about gradient descent) and chapter 11 (we will use this next week)
o Video on gradient descent at URL:"https://www.youtube.com/watch?v=sDv4f4s2SB8"
o Video on stochastic gradient descent at URL:"https://www.youtube.com/watch?v=vMh0zPT0tLI"
o Neural Networks demystified at URL:"https://www.youtube.com/watch?v=bxe2T-V8XRs&list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU&ab_channel=WelchLabs"