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layout: default
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title: DEEP LEARNING WITH PYTORCH
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author: Alfredo Canziani
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translator: Huynh Nguyen
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lang-ref: home
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---
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**DS-GA 1008 · SPRING 2020 · [NYU CENTER FOR DATA SCIENCE](http://cds.nyu.edu/)**
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| INSTRUCTORS | Yann LeCun & Alfredo Canziani |
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| LECTURES | Mondays 16:55 – 18:35, [GCASL C95](http://library.nyu.edu/services/campus-media/classrooms/gcasl-c95/) |
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| PRACTICA | Tuesdays 19:10 – 20:00, [GCASL C95](http://library.nyu.edu/services/campus-media/classrooms/gcasl-c95/) |
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| [PIAZZA](https://piazza.com/nyu/spring2020/dsga1008/home) | Access code: `DLSP20` |
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| MATERIAL | [Google Drive](https://bitly.com/DLSP20), [Notebooks](https://github.com/Atcold/pytorch-Deep-Learning) |
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## Description
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This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include: [DS-GA 1001 Intro to Data Science](https://cds.nyu.edu/academics/ms-curriculum/) or a graduate-level machine learning course.
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## Lectures
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**Legend**: 🖥 slides, 📓 Jupyter notebook, 🎥 YouTube video.
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<table>
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<!-- =============================== HEADER ================================ -->
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<thead>
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<tr>
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<th>Week</th>
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<th align="left">Format</th>
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<th align="left">Title</th>
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<th align="left">Resources</th>
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</tr>
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</thead>
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<tbody>
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<!-- =============================== WEEK 1 ================================ -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week01/01">①</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week01/01-1">History and motivation</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/open?id=1Q7LtZyIS1f3TfeTGll3aDtWygh3GAfCb">🖥️</a>
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<a href="https://www.youtube.com/watch?v=0bMe_vCZo30">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week01/01-2">Evolution and DL</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week01/01-3">Neural nets (NN)</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/01-tensor_tutorial.ipynb">📓</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/02-space_stretching.ipynb">📓</a>
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<a href="https://www.youtube.com/watch?v=5_qrxVq1kvc">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 2 ================================ -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week02/02">②</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week02/02-1">SGD and backprop</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/open?id=1w2jV_BT2hWzfOKBR02x_rB4-dfVUI6SR">🖥️</a>
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<a href="https://www.youtube.com/watch?v=d9vdh3b787Y">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week02/02-2">Backprop in practice</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week02/02-3">NN training</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/slides/01%20-%20Spiral%20classification.pdf">🖥</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/04-spiral_classification.ipynb">📓</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/05-regression.ipynb">📓</a>
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<a href="https://www.youtube.com/watch?v=WAn6lip5oWk">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 3 ================================ -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week03/03">③</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week03/03-1">Parameter transformation</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/open?id=18UFaOGNKKKO5TYnSxr2b8dryI-PgZQmC">🖥️</a>
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<a href="https://youtu.be/FW5gFiJb-ig">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week03/03-2">CNN</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week03/03-3">Natural signals' properties</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/slides/02%20-%20CNN.pdf">🖥</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/06-convnet.ipynb">📓</a>
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<a href="https://youtu.be/kwPWpVverkw">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 4 ================================ -->
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<tr>
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<td rowspan="1" align="center"><a href="en/week04/04">④</a></td>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week04/04-1">1D convolutions</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/07-listening_to_kernels.ipynb">📓</a>
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<a href="https://youtu.be/OrBEon3VlQg">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 5 ================================ -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week05/05">⑤</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week05/05-1">Optimisation I</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/open?id=1pwlGN6hDFfEYQqBqcMjWbe4yfBDTxsab">🖥️</a>
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<a href="https://youtu.be/--NZb480zlg">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week05/05-2">Optimisation II</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week05/05-3">CNN, autograd</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/03-autograd_tutorial.ipynb">📓</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/extra/b-custom_grads.ipynb">📓</a>
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<a href="https://youtu.be/eEzCZnOFU1w">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 6 ================================ -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week06/06">⑥</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week06/06-1">CNN applications</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/open?id=1opT7lV0IRYJegtZjuHsKhlsM5L7GpGL1">🖥️</a>
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<a href="https://drive.google.com/open?id=1sdeVBC3nuh5Zkm2sqzdScEicRvLc_v-F">🖥️</a>
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<a href="https://youtu.be/ycbMGyCPzvE">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week06/06-2">RNNs and attention</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week06/06-3">Training RNNs</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/08-seq_classification.ipynb">📓</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/09-echo_data.ipynb">📓</a>
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<a href="https://youtu.be/8cAffg2jaT0">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 7 ================================ -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week07/07">⑦</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week07/07-1">Energy-Based Models</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/open?id=1z8Dz1YtkOEJpU-gh5RIjORs3GGqkYJQa">🖥️</a>
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<a href="https://youtu.be/tVwV14YkbYs">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week07/07-2">SSL, EBM</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week07/07-3">Autoencoders</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/slides/05%20-%20Generative%20models.pdf">🖥️</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/10-autoencoder.ipynb">📓</a>
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<a href="https://youtu.be/bggWQ14DD9M">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 8 ================================ -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week08/08">⑧</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week08/08-1">Contrastive methods</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/open?id=1Zo_PyBEO6aNt0GV74kj8MQL7kfHdIHYO">🖥️</a>
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<a href="https://youtu.be/ZaVP2SY23nc">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week08/08-2">Regularised latent</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week08/08-3">Training VAEs</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/slides/05%20-%20Generative%20models.pdf">🖥️</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/11-VAE.ipynb">📓</a>
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<a href="https://youtu.be/7Rb4s9wNOmc">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 9 ================================ -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week09/09">⑨</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week09/09-1">Sparsity</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/open?id=1wJRzhjSqlrSqEpX4Omagb_gdIkQ5f-6K">🖥️</a>
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<a href="https://youtu.be/Pgct8PKV7iw">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week09/09-2">Word model, GANs</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week09/09-3">Training GANs</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/slides/05%20-%20Generative%20models.pdf">🖥️</a>
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<a href="https://github.com/pytorch/examples/tree/master/dcgan">📓</a>
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<a href="https://youtu.be/xYc11zyZ26M">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 10 =============================== -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week10/10">⑩</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week10/10-1">CV SSL I</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/open?id=16lsnDN2HIBTcRucbVKY5B_U16c0tNQhR">🖥️</a>
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<a href="https://youtu.be/0KeR6i1_56g">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week10/10-2">CV SSL II</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week10/10-3">Predictive Control</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/slides/09%20-%20Controller%20learning.pdf">🖥️</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/14-truck_backer-upper.ipynb">📓</a>
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<a href="https://youtu.be/A3klBqEWR-I">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 11 =============================== -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week11/11">⑪</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week11/11-1">Activations</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/file/d/1AzFVLG7D4NK6ugh60f0cJQGYF5OL2sUB">🖥️</a>
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<a href="https://drive.google.com/file/d/1rkiZy0vjZqE2w7baVWvxwfAGae0Eh1Wm">🖥️</a>
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<a href="https://drive.google.com/file/d/1tryOlVAFmazLLZusD2-UfReFMkPk5hPk">🖥️</a>
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<a href="https://youtu.be/bj1fh3BvqSU">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week11/11-2">Losses</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week11/11-3">PPUU</a></td>
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<td>
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<a href="http://bit.ly/PPUU-slides">🖥️</a>
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<a href="http://bit.ly/PPUU-code">📓</a>
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<a href="https://youtu.be/VcrCr-KNBHc">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 12 =============================== -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week12/12">⑫</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week12/12-1">DL for NLP I</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/file/d/149m3wRavTp4DQZ6RJTej8KP8gv4jnkPW/">🖥️</a>
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<a href="https://youtu.be/6D4EWKJgNn0">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week12/12-2">DL for NLP II</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week12/12-3">Attention & transformer</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/slides/10%20-%20Attention%20%26%20transformer.pdf">🖥️</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/15-transformer.ipynb">📓</a>
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<a href="https://youtu.be/f01J0Dri-6k">🎥</a>
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</td>
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</tr>
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<!-- =============================== WEEK 13 =============================== -->
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<tr>
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<td rowspan="3" align="center"><a href="en/week13/13">⑬</a></td>
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<td rowspan="2">Lecture</td>
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<td><a href="en/week13/13-1">GCNs I</a></td>
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<td rowspan="2">
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<a href="https://drive.google.com/file/d/1oq-nZE2bEiQjqBlmk5_N_rFC8LQY0jQr/">🖥️</a>
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<a href="https://youtu.be/Iiv9R6BjxHM">🎥</a>
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</td>
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</tr>
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<tr><td><a href="en/week13/13-2">GCNs II</a></td></tr>
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<tr>
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<td rowspan="1">Practicum</td>
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<td><a href="en/week13/13-3">GCNs III</a></td>
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<td>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/slides/11%20-%20GCN.pdf">🖥️</a>
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<a href="https://github.com/Atcold/pytorch-Deep-Learning/blob/master/16-gated_GCN.ipynb">📓</a>
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<a href="https://youtu.be/2aKXWqkbpWg">🎥</a>
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</td>
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</tr>
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</tbody>
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</table>
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## People
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| Role | Photo | Contact | About |
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|:-----|:-----:|:--------|:------|
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|Instructor|<img src="images/Yann.png" width="100" height="100">|<a href="https://twitter.com/ylecun">Yann LeCun</a><br>[email protected]|Silver Professor in CS at NYU<br>and Turing Award winner|
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|Instructor|<img src="https://avatars1.githubusercontent.com/u/2119355" width="100" height="100">|<a href="https://twitter.com/alfcnz">Alfredo Canziani</a><br>[email protected]|Asst. Prof. in CS at NYU|
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|Assistant|<img src="https://pbs.twimg.com/profile_images/1186879808845860864/czRv3g1G_400x400.jpg" width="100" height="100">|<a href="https://twitter.com/marikgoldstein">Mark Goldstein</a><br>[email protected]|PhD student in CS at NYU|
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|Webmaster|<img src="https://pbs.twimg.com/profile_images/673997980370927616/vMXf545j_400x400.jpg" width="100" height="100">|<a href="https://twitter.com/ebetica">Zeming Lin</a><br>[email protected]|PhD student in CS at NYU|
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|Grader|<img src="https://st3.depositphotos.com/13159112/17145/v/450/depositphotos_171453724-stock-illustration-default-avatar-profile-icon-grey.jpg" width="100" height="100">|Serkan Karakulak <br>[email protected]|
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|Grader|<img src="https://st3.depositphotos.com/13159112/17145/v/450/depositphotos_171453724-stock-illustration-default-avatar-profile-icon-grey.jpg" width="100" height="100">|Raghav Jajodia <br>[email protected]|
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|Grader|<img src="https://st3.depositphotos.com/13159112/17145/v/450/depositphotos_171453724-stock-illustration-default-avatar-profile-icon-grey.jpg" width="100" height="100">|Priyank Pathak <br>[email protected]|
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|Grader|<img src="https://st3.depositphotos.com/13159112/17145/v/450/depositphotos_171453724-stock-illustration-default-avatar-profile-icon-grey.jpg" width="100" height="100">|Chiao-Hsun Wang <br>[email protected]|
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|Grader|<img src="https://st3.depositphotos.com/13159112/17145/v/450/depositphotos_171453724-stock-illustration-default-avatar-profile-icon-grey.jpg" width="100" height="100">|Pedro Vidal<br>[email protected]|
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|Grader|<img src="https://st3.depositphotos.com/13159112/17145/v/450/depositphotos_171453724-stock-illustration-default-avatar-profile-icon-grey.jpg" width="100" height="100">|Bixing Yan <br>[email protected]|

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