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‎doc/pub/week37/html/._week37-bs000.html‎

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'adam-algorithm-taken-from-goodfellow-et-al-https-www-deeplearningbook-org-contents-optimization-html'),
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('Practical tips', 2, None, 'practical-tips'),
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('Sneaking in auotmatic differentiation using Autograd',
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('Sneaking in automatic differentiation using Autograd',
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2,
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None,
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'sneaking-in-auotmatic-differentiation-using-autograd'),
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'sneaking-in-automatic-differentiation-using-autograd'),
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('Same code but now with momentum gradient descent',
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None,
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2,
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None,
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'same-code-but-now-with-momentum-gradient-descent'),
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("But none of these can compete with Newton's method",
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2,
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None,
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'but-none-of-these-can-compete-with-newton-s-method'),
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('Similar (second order function now) problem but now with '
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'AdaGrad',
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('Material for the lab sessions',
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None,
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'material-for-the-lab-sessions')]}
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'material-for-the-lab-sessions'),
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('Reminder on different scaling methods',
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2,
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None,
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'reminder-on-different-scaling-methods'),
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('Functionality in Scikit-Learn',
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2,
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None,
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'functionality-in-scikit-learn'),
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('More preprocessing', 2, None, 'more-preprocessing'),
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('Frequently used scaling functions',
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None,
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'frequently-used-scaling-functions')]}
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<body>
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<!-- navigation toc: --> <li><a href="._week37-bs038.html#rmsprop-algorithm-taken-from-goodfellow-et-al-https-www-deeplearningbook-org-contents-optimization-html" style="font-size: 80%;">RMSProp algorithm, taken from "Goodfellow et al":"https://www.deeplearningbook.org/contents/optimization.html"</a></li>
259276
<!-- navigation toc: --> <li><a href="._week37-bs038.html#adam-algorithm-taken-from-goodfellow-et-al-https-www-deeplearningbook-org-contents-optimization-html" style="font-size: 80%;">ADAM algorithm, taken from "Goodfellow et al":"https://www.deeplearningbook.org/contents/optimization.html"</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs039.html#practical-tips" style="font-size: 80%;">Practical tips</a></li>
261-
<!-- navigation toc: --> <li><a href="._week37-bs040.html#sneaking-in-auotmatic-differentiation-using-autograd" style="font-size: 80%;">Sneaking in auotmatic differentiation using Autograd</a></li>
278+
<!-- navigation toc: --> <li><a href="._week37-bs040.html#sneaking-in-automatic-differentiation-using-autograd" style="font-size: 80%;">Sneaking in automatic differentiation using Autograd</a></li>
262279
<!-- navigation toc: --> <li><a href="._week37-bs043.html#same-code-but-now-with-momentum-gradient-descent" style="font-size: 80%;">Same code but now with momentum gradient descent</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs042.html#including-stochastic-gradient-descent-with-autograd" style="font-size: 80%;">Including Stochastic Gradient Descent with Autograd</a></li>
264281
<!-- navigation toc: --> <li><a href="._week37-bs043.html#same-code-but-now-with-momentum-gradient-descent" style="font-size: 80%;">Same code but now with momentum gradient descent</a></li>
265-
<!-- navigation toc: --> <li><a href="._week37-bs044.html#similar-second-order-function-now-problem-but-now-with-adagrad" style="font-size: 80%;">Similar (second order function now) problem but now with AdaGrad</a></li>
266-
<!-- navigation toc: --> <li><a href="._week37-bs045.html#rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent" style="font-size: 80%;">RMSprop for adaptive learning rate with Stochastic Gradient Descent</a></li>
267-
<!-- navigation toc: --> <li><a href="._week37-bs046.html#and-finally-adam-https-arxiv-org-pdf-1412-6980-pdf" style="font-size: 80%;">And finally "ADAM":"https://arxiv.org/pdf/1412.6980.pdf"</a></li>
268-
<!-- navigation toc: --> <li><a href="._week37-bs047.html#material-for-the-lab-sessions" style="font-size: 80%;">Material for the lab sessions</a></li>
282+
<!-- navigation toc: --> <li><a href="._week37-bs044.html#but-none-of-these-can-compete-with-newton-s-method" style="font-size: 80%;">But none of these can compete with Newton's method</a></li>
283+
<!-- navigation toc: --> <li><a href="._week37-bs045.html#similar-second-order-function-now-problem-but-now-with-adagrad" style="font-size: 80%;">Similar (second order function now) problem but now with AdaGrad</a></li>
284+
<!-- navigation toc: --> <li><a href="._week37-bs046.html#rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent" style="font-size: 80%;">RMSprop for adaptive learning rate with Stochastic Gradient Descent</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs047.html#and-finally-adam-https-arxiv-org-pdf-1412-6980-pdf" style="font-size: 80%;">And finally "ADAM":"https://arxiv.org/pdf/1412.6980.pdf"</a></li>
286+
<!-- navigation toc: --> <li><a href="._week37-bs048.html#material-for-the-lab-sessions" style="font-size: 80%;">Material for the lab sessions</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs049.html#reminder-on-different-scaling-methods" style="font-size: 80%;">Reminder on different scaling methods</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs050.html#functionality-in-scikit-learn" style="font-size: 80%;">Functionality in Scikit-Learn</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs051.html#more-preprocessing" style="font-size: 80%;">More preprocessing</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs052.html#frequently-used-scaling-functions" style="font-size: 80%;">Frequently used scaling functions</a></li>
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</ul>
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<li><a href="._week37-bs008.html">9</a></li>
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<li><a href="._week37-bs009.html">10</a></li>
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<li><a href="">...</a></li>
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<!-- ------------------- end of main content --------------- -->

‎doc/pub/week37/html/._week37-bs001.html‎

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'adam-algorithm-taken-from-goodfellow-et-al-https-www-deeplearningbook-org-contents-optimization-html'),
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('Practical tips', 2, None, 'practical-tips'),
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('Sneaking in auotmatic differentiation using Autograd',
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('Sneaking in automatic differentiation using Autograd',
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2,
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None,
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'sneaking-in-auotmatic-differentiation-using-autograd'),
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'sneaking-in-automatic-differentiation-using-autograd'),
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('Same code but now with momentum gradient descent',
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2,
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None,
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2,
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None,
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'same-code-but-now-with-momentum-gradient-descent'),
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("But none of these can compete with Newton's method",
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None,
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'but-none-of-these-can-compete-with-newton-s-method'),
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('Similar (second order function now) problem but now with '
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'AdaGrad',
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('Material for the lab sessions',
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'material-for-the-lab-sessions')]}
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'material-for-the-lab-sessions'),
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('Reminder on different scaling methods',
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None,
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'reminder-on-different-scaling-methods'),
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('Functionality in Scikit-Learn',
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2,
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None,
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'functionality-in-scikit-learn'),
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('More preprocessing', 2, None, 'more-preprocessing'),
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('Frequently used scaling functions',
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'frequently-used-scaling-functions')]}
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<!-- navigation toc: --> <li><a href="._week37-bs038.html#rmsprop-algorithm-taken-from-goodfellow-et-al-https-www-deeplearningbook-org-contents-optimization-html" style="font-size: 80%;">RMSProp algorithm, taken from "Goodfellow et al":"https://www.deeplearningbook.org/contents/optimization.html"</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs038.html#adam-algorithm-taken-from-goodfellow-et-al-https-www-deeplearningbook-org-contents-optimization-html" style="font-size: 80%;">ADAM algorithm, taken from "Goodfellow et al":"https://www.deeplearningbook.org/contents/optimization.html"</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs039.html#practical-tips" style="font-size: 80%;">Practical tips</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs040.html#sneaking-in-auotmatic-differentiation-using-autograd" style="font-size: 80%;">Sneaking in auotmatic differentiation using Autograd</a></li>
278+
<!-- navigation toc: --> <li><a href="._week37-bs040.html#sneaking-in-automatic-differentiation-using-autograd" style="font-size: 80%;">Sneaking in automatic differentiation using Autograd</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs043.html#same-code-but-now-with-momentum-gradient-descent" style="font-size: 80%;">Same code but now with momentum gradient descent</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs042.html#including-stochastic-gradient-descent-with-autograd" style="font-size: 80%;">Including Stochastic Gradient Descent with Autograd</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs043.html#same-code-but-now-with-momentum-gradient-descent" style="font-size: 80%;">Same code but now with momentum gradient descent</a></li>
265-
<!-- navigation toc: --> <li><a href="._week37-bs044.html#similar-second-order-function-now-problem-but-now-with-adagrad" style="font-size: 80%;">Similar (second order function now) problem but now with AdaGrad</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs045.html#rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent" style="font-size: 80%;">RMSprop for adaptive learning rate with Stochastic Gradient Descent</a></li>
267-
<!-- navigation toc: --> <li><a href="._week37-bs046.html#and-finally-adam-https-arxiv-org-pdf-1412-6980-pdf" style="font-size: 80%;">And finally "ADAM":"https://arxiv.org/pdf/1412.6980.pdf"</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs047.html#material-for-the-lab-sessions" style="font-size: 80%;">Material for the lab sessions</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs044.html#but-none-of-these-can-compete-with-newton-s-method" style="font-size: 80%;">But none of these can compete with Newton's method</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs045.html#similar-second-order-function-now-problem-but-now-with-adagrad" style="font-size: 80%;">Similar (second order function now) problem but now with AdaGrad</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs046.html#rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent" style="font-size: 80%;">RMSprop for adaptive learning rate with Stochastic Gradient Descent</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs047.html#and-finally-adam-https-arxiv-org-pdf-1412-6980-pdf" style="font-size: 80%;">And finally "ADAM":"https://arxiv.org/pdf/1412.6980.pdf"</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs048.html#material-for-the-lab-sessions" style="font-size: 80%;">Material for the lab sessions</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs049.html#reminder-on-different-scaling-methods" style="font-size: 80%;">Reminder on different scaling methods</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs050.html#functionality-in-scikit-learn" style="font-size: 80%;">Functionality in Scikit-Learn</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs051.html#more-preprocessing" style="font-size: 80%;">More preprocessing</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs052.html#frequently-used-scaling-functions" style="font-size: 80%;">Frequently used scaling functions</a></li>
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<li><a href="._week37-bs002.html">&raquo;</a></li>
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<!-- ------------------- end of main content --------------- -->

‎doc/pub/week37/html/._week37-bs002.html‎

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'adam-algorithm-taken-from-goodfellow-et-al-https-www-deeplearningbook-org-contents-optimization-html'),
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('Practical tips', 2, None, 'practical-tips'),
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('Sneaking in auotmatic differentiation using Autograd',
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('Sneaking in automatic differentiation using Autograd',
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2,
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None,
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'sneaking-in-auotmatic-differentiation-using-autograd'),
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'sneaking-in-automatic-differentiation-using-autograd'),
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('Same code but now with momentum gradient descent',
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2,
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None,
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None,
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'same-code-but-now-with-momentum-gradient-descent'),
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("But none of these can compete with Newton's method",
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2,
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None,
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'but-none-of-these-can-compete-with-newton-s-method'),
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('Similar (second order function now) problem but now with '
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'AdaGrad',
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2,
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('Material for the lab sessions',
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'material-for-the-lab-sessions')]}
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'material-for-the-lab-sessions'),
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('Reminder on different scaling methods',
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2,
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None,
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'reminder-on-different-scaling-methods'),
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('Functionality in Scikit-Learn',
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2,
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None,
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'functionality-in-scikit-learn'),
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('More preprocessing', 2, None, 'more-preprocessing'),
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('Frequently used scaling functions',
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None,
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'frequently-used-scaling-functions')]}
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<!-- navigation toc: --> <li><a href="._week37-bs038.html#rmsprop-algorithm-taken-from-goodfellow-et-al-https-www-deeplearningbook-org-contents-optimization-html" style="font-size: 80%;">RMSProp algorithm, taken from "Goodfellow et al":"https://www.deeplearningbook.org/contents/optimization.html"</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs038.html#adam-algorithm-taken-from-goodfellow-et-al-https-www-deeplearningbook-org-contents-optimization-html" style="font-size: 80%;">ADAM algorithm, taken from "Goodfellow et al":"https://www.deeplearningbook.org/contents/optimization.html"</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs039.html#practical-tips" style="font-size: 80%;">Practical tips</a></li>
261-
<!-- navigation toc: --> <li><a href="._week37-bs040.html#sneaking-in-auotmatic-differentiation-using-autograd" style="font-size: 80%;">Sneaking in auotmatic differentiation using Autograd</a></li>
278+
<!-- navigation toc: --> <li><a href="._week37-bs040.html#sneaking-in-automatic-differentiation-using-autograd" style="font-size: 80%;">Sneaking in automatic differentiation using Autograd</a></li>
262279
<!-- navigation toc: --> <li><a href="._week37-bs043.html#same-code-but-now-with-momentum-gradient-descent" style="font-size: 80%;">Same code but now with momentum gradient descent</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs042.html#including-stochastic-gradient-descent-with-autograd" style="font-size: 80%;">Including Stochastic Gradient Descent with Autograd</a></li>
264281
<!-- navigation toc: --> <li><a href="._week37-bs043.html#same-code-but-now-with-momentum-gradient-descent" style="font-size: 80%;">Same code but now with momentum gradient descent</a></li>
265-
<!-- navigation toc: --> <li><a href="._week37-bs044.html#similar-second-order-function-now-problem-but-now-with-adagrad" style="font-size: 80%;">Similar (second order function now) problem but now with AdaGrad</a></li>
266-
<!-- navigation toc: --> <li><a href="._week37-bs045.html#rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent" style="font-size: 80%;">RMSprop for adaptive learning rate with Stochastic Gradient Descent</a></li>
267-
<!-- navigation toc: --> <li><a href="._week37-bs046.html#and-finally-adam-https-arxiv-org-pdf-1412-6980-pdf" style="font-size: 80%;">And finally "ADAM":"https://arxiv.org/pdf/1412.6980.pdf"</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs047.html#material-for-the-lab-sessions" style="font-size: 80%;">Material for the lab sessions</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs044.html#but-none-of-these-can-compete-with-newton-s-method" style="font-size: 80%;">But none of these can compete with Newton's method</a></li>
283+
<!-- navigation toc: --> <li><a href="._week37-bs045.html#similar-second-order-function-now-problem-but-now-with-adagrad" style="font-size: 80%;">Similar (second order function now) problem but now with AdaGrad</a></li>
284+
<!-- navigation toc: --> <li><a href="._week37-bs046.html#rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent" style="font-size: 80%;">RMSprop for adaptive learning rate with Stochastic Gradient Descent</a></li>
285+
<!-- navigation toc: --> <li><a href="._week37-bs047.html#and-finally-adam-https-arxiv-org-pdf-1412-6980-pdf" style="font-size: 80%;">And finally "ADAM":"https://arxiv.org/pdf/1412.6980.pdf"</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs048.html#material-for-the-lab-sessions" style="font-size: 80%;">Material for the lab sessions</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs049.html#reminder-on-different-scaling-methods" style="font-size: 80%;">Reminder on different scaling methods</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs050.html#functionality-in-scikit-learn" style="font-size: 80%;">Functionality in Scikit-Learn</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs051.html#more-preprocessing" style="font-size: 80%;">More preprocessing</a></li>
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<!-- navigation toc: --> <li><a href="._week37-bs052.html#frequently-used-scaling-functions" style="font-size: 80%;">Frequently used scaling functions</a></li>
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<!-- ------------------- end of main content --------------- -->

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