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‎doc/LectureNotes/week46.ipynb‎

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‎doc/pub/week46/html/._week46-bs000.html‎

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('The mathematics of RNNs, the basic architecture',
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2,
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None,
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'the-mathematics-of-rnns-the-basic-architecture'),
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('Gating mechanism: Long Short Term Memory (LSTM)',
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'gating-mechanism-long-short-term-memory-lstm'),
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('Implementing a memory cell in a neural network',
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('LSTM details', 2, None, 'lstm-details'),
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('Basic layout (All figures from Raschka *et al.,*)',
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2,
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None,
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'basic-layout-all-figures-from-raschka-et-al'),
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('LSTM details', 2, None, 'lstm-details'),
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('Comparing with a standard RNN',
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2,
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None,
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'comparing-with-a-standard-rnn'),
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('LSTM details I', 2, None, 'lstm-details-i'),
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('LSTM details II', 2, None, 'lstm-details-ii'),
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('LSTM details III', 2, None, 'lstm-details-iii'),
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('Forget gate', 2, None, 'forget-gate'),
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('The forget gate', 2, None, 'the-forget-gate'),
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('Basic layout', 2, None, 'basic-layout'),
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('Input gate', 2, None, 'input-gate'),
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('Short summary', 2, None, 'short-summary'),
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('Forget and input', 2, None, 'forget-and-input'),
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('Basic layout', 2, None, 'basic-layout'),
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('Output gate', 2, None, 'output-gate'),
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('Summary of LSTM', 2, None, 'summary-of-lstm'),
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('LSTM implementation using TensorFlow',
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2,
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None,
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'lstm-implementation-using-tensorflow'),
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('And the corresponding one with PyTorch',
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2,
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None,
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'and-the-corresponding-one-with-pytorch'),
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('Dynamical ordinary differential equation',
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2,
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None,
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'dynamical-ordinary-differential-equation'),
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('The Runge-Kutta-4 code', 2, None, 'the-runge-kutta-4-code'),
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('Using the above data to train an RNN',
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2,
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None,
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'using-the-above-data-to-train-an-rnn')]}
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'the-mathematics-of-rnns-the-basic-architecture')]}
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end of tocinfo -->
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<body>
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<!-- navigation toc: --> <li><a href="._week46-bs041.html#summary-of-a-typical-rnn" style="font-size: 80%;">Summary of a typical RNN</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs042.html#four-effective-ways-to-learn-an-rnn" style="font-size: 80%;">Four effective ways to learn an RNN</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs043.html#the-mathematics-of-rnns-the-basic-architecture" style="font-size: 80%;">The mathematics of RNNs, the basic architecture</a></li>
286-
<!-- navigation toc: --> <li><a href="._week46-bs044.html#gating-mechanism-long-short-term-memory-lstm" style="font-size: 80%;">Gating mechanism: Long Short Term Memory (LSTM)</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs045.html#implementing-a-memory-cell-in-a-neural-network" style="font-size: 80%;">Implementing a memory cell in a neural network</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs048.html#lstm-details" style="font-size: 80%;">LSTM details</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs047.html#basic-layout-all-figures-from-raschka-et-al" style="font-size: 80%;">Basic layout (All figures from Raschka <em>et al.,</em>)</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs048.html#lstm-details" style="font-size: 80%;">LSTM details</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs049.html#comparing-with-a-standard-rnn" style="font-size: 80%;">Comparing with a standard RNN</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs050.html#lstm-details-i" style="font-size: 80%;">LSTM details I</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs051.html#lstm-details-ii" style="font-size: 80%;">LSTM details II</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs052.html#lstm-details-iii" style="font-size: 80%;">LSTM details III</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs053.html#forget-gate" style="font-size: 80%;">Forget gate</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs054.html#the-forget-gate" style="font-size: 80%;">The forget gate</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs059.html#basic-layout" style="font-size: 80%;">Basic layout</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs056.html#input-gate" style="font-size: 80%;">Input gate</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs057.html#short-summary" style="font-size: 80%;">Short summary</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs058.html#forget-and-input" style="font-size: 80%;">Forget and input</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs059.html#basic-layout" style="font-size: 80%;">Basic layout</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs060.html#output-gate" style="font-size: 80%;">Output gate</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs061.html#summary-of-lstm" style="font-size: 80%;">Summary of LSTM</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs062.html#lstm-implementation-using-tensorflow" style="font-size: 80%;">LSTM implementation using TensorFlow</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs063.html#and-the-corresponding-one-with-pytorch" style="font-size: 80%;">And the corresponding one with PyTorch</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs064.html#dynamical-ordinary-differential-equation" style="font-size: 80%;">Dynamical ordinary differential equation</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs065.html#the-runge-kutta-4-code" style="font-size: 80%;">The Runge-Kutta-4 code</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs066.html#using-the-above-data-to-train-an-rnn" style="font-size: 80%;">Using the above data to train an RNN</a></li>
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<li><a href="._week46-bs008.html">9</a></li>
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<li><a href="._week46-bs009.html">10</a></li>
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<li><a href="">...</a></li>
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<li><a href="._week46-bs066.html">67</a></li>
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<li><a href="._week46-bs043.html">44</a></li>
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<li><a href="._week46-bs001.html">&raquo;</a></li>
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<!-- ------------------- end of main content --------------- -->

‎doc/pub/week46/html/._week46-bs001.html‎

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('The mathematics of RNNs, the basic architecture',
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2,
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None,
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'the-mathematics-of-rnns-the-basic-architecture'),
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('Gating mechanism: Long Short Term Memory (LSTM)',
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2,
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None,
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'gating-mechanism-long-short-term-memory-lstm'),
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('Implementing a memory cell in a neural network',
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2,
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None,
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'implementing-a-memory-cell-in-a-neural-network'),
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('LSTM details', 2, None, 'lstm-details'),
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('Basic layout (All figures from Raschka *et al.,*)',
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2,
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None,
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'basic-layout-all-figures-from-raschka-et-al'),
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('LSTM details', 2, None, 'lstm-details'),
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('Comparing with a standard RNN',
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2,
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None,
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'comparing-with-a-standard-rnn'),
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('LSTM details I', 2, None, 'lstm-details-i'),
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('LSTM details II', 2, None, 'lstm-details-ii'),
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('LSTM details III', 2, None, 'lstm-details-iii'),
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('Forget gate', 2, None, 'forget-gate'),
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('The forget gate', 2, None, 'the-forget-gate'),
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('Basic layout', 2, None, 'basic-layout'),
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('Input gate', 2, None, 'input-gate'),
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('Short summary', 2, None, 'short-summary'),
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('Forget and input', 2, None, 'forget-and-input'),
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('Basic layout', 2, None, 'basic-layout'),
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('Output gate', 2, None, 'output-gate'),
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('Summary of LSTM', 2, None, 'summary-of-lstm'),
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('LSTM implementation using TensorFlow',
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2,
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None,
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'lstm-implementation-using-tensorflow'),
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('And the corresponding one with PyTorch',
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2,
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None,
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'and-the-corresponding-one-with-pytorch'),
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('Dynamical ordinary differential equation',
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2,
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None,
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'dynamical-ordinary-differential-equation'),
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('The Runge-Kutta-4 code', 2, None, 'the-runge-kutta-4-code'),
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('Using the above data to train an RNN',
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2,
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None,
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'using-the-above-data-to-train-an-rnn')]}
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'the-mathematics-of-rnns-the-basic-architecture')]}
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end of tocinfo -->
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<!-- navigation toc: --> <li><a href="._week46-bs041.html#summary-of-a-typical-rnn" style="font-size: 80%;">Summary of a typical RNN</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs042.html#four-effective-ways-to-learn-an-rnn" style="font-size: 80%;">Four effective ways to learn an RNN</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs043.html#the-mathematics-of-rnns-the-basic-architecture" style="font-size: 80%;">The mathematics of RNNs, the basic architecture</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs044.html#gating-mechanism-long-short-term-memory-lstm" style="font-size: 80%;">Gating mechanism: Long Short Term Memory (LSTM)</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs045.html#implementing-a-memory-cell-in-a-neural-network" style="font-size: 80%;">Implementing a memory cell in a neural network</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs048.html#lstm-details" style="font-size: 80%;">LSTM details</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs047.html#basic-layout-all-figures-from-raschka-et-al" style="font-size: 80%;">Basic layout (All figures from Raschka <em>et al.,</em>)</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs048.html#lstm-details" style="font-size: 80%;">LSTM details</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs049.html#comparing-with-a-standard-rnn" style="font-size: 80%;">Comparing with a standard RNN</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs050.html#lstm-details-i" style="font-size: 80%;">LSTM details I</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs051.html#lstm-details-ii" style="font-size: 80%;">LSTM details II</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs052.html#lstm-details-iii" style="font-size: 80%;">LSTM details III</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs053.html#forget-gate" style="font-size: 80%;">Forget gate</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs054.html#the-forget-gate" style="font-size: 80%;">The forget gate</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs059.html#basic-layout" style="font-size: 80%;">Basic layout</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs056.html#input-gate" style="font-size: 80%;">Input gate</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs057.html#short-summary" style="font-size: 80%;">Short summary</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs058.html#forget-and-input" style="font-size: 80%;">Forget and input</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs059.html#basic-layout" style="font-size: 80%;">Basic layout</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs060.html#output-gate" style="font-size: 80%;">Output gate</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs061.html#summary-of-lstm" style="font-size: 80%;">Summary of LSTM</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs062.html#lstm-implementation-using-tensorflow" style="font-size: 80%;">LSTM implementation using TensorFlow</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs063.html#and-the-corresponding-one-with-pytorch" style="font-size: 80%;">And the corresponding one with PyTorch</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs064.html#dynamical-ordinary-differential-equation" style="font-size: 80%;">Dynamical ordinary differential equation</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs065.html#the-runge-kutta-4-code" style="font-size: 80%;">The Runge-Kutta-4 code</a></li>
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<!-- navigation toc: --> <li><a href="._week46-bs066.html#using-the-above-data-to-train-an-rnn" style="font-size: 80%;">Using the above data to train an RNN</a></li>
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<!-- subsequent paragraphs come in larger fonts, so start with a paragraph -->
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<ol>
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<li> Intro to and mathematics of Recurrent Neural Networks (RNNs)</li>
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<li> Lecture notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week46/ipynb/week46.ipynb" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week46/ipynb/week46.ipynb</tt></a>
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<!-- o Video of lecture at <a href="https://youtu.be/TfRKUfdJwB4" target="_self"><tt>https://youtu.be/TfRKUfdJwB4</tt></a> -->
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<!-- o Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesNovember11.pdf" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2024/NotesNovember11.pdf</tt></a> --></li>
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<li> Lecture notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week46/ipynb/week46.ipynb" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/pub/week46/ipynb/week46.ipynb</tt></a></li>
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<li> Video of lecture at <a href="https://youtu.be/WNWKaBbqOpg" target="_self"><tt>https://youtu.be/WNWKaBbqOpg</tt></a></li>
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<li> Whiteboard notes at <a href="https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek46.pdf" target="_self"><tt>https://github.com/CompPhysics/MachineLearning/blob/master/doc/HandWrittenNotes/2025/FYSSTKweek46.pdf</tt></a></li>
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<li><a href="._week46-bs009.html">10</a></li>
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